Overview

Brought to you by YData

Dataset statistics

	Dataset A	Dataset B
Number of variables	74	74
Number of observations	4.365	1.339
Missing cells	91.121	31.123
Missing cells (%)	28.2%	31.4%
Total size in memory	2.6 MiB	816.9 KiB
Average record size in memory	630.3 B	624.7 B

Variable types

	Dataset A	Dataset B
Numeric	41	41
Text	28	28
Unsupported	5	5

Alerts

Dataset A	Dataset B
`AgeDecade` has 137 (3.1%) missing values	`AgeDecade` has 107 (8.0%) missing values	Missing
`AgeMonths` has 2358 (54.0%) missing values	`AgeMonths` has 666 (49.7%) missing values	Missing
`Race3` has 2077 (47.6%) missing values	`Race3` has 722 (53.9%) missing values	Missing
`HHIncome` has 301 (6.9%) missing values	`HHIncome` has 173 (12.9%) missing values	Missing
`HHIncomeMid` has 301 (6.9%) missing values	`HHIncomeMid` has 173 (12.9%) missing values	Missing
`Poverty` has 259 (5.9%) missing values	`Poverty` has 154 (11.5%) missing values	Missing
`Length` has 4365 (100.0%) missing values	`Length` has 1339 (100.0%) missing values	Missing
`HeadCirc` has 4365 (100.0%) missing values	`HeadCirc` has 1339 (100.0%) missing values	Missing
`BMICatUnder20yrs` has 4365 (100.0%) missing values	`BMICatUnder20yrs` has 1339 (100.0%) missing values	Missing
`BMI_WHO` has 57 (1.3%) missing values	`BMI_WHO` has 18 (1.3%) missing values	Missing
`Pulse` has 147 (3.4%) missing values	`Pulse` has 48 (3.6%) missing values	Missing
`BPSysAve` has 154 (3.5%) missing values	`BPSysAve` has 50 (3.7%) missing values	Missing
`BPDiaAve` has 154 (3.5%) missing values	`BPDiaAve` has 50 (3.7%) missing values	Missing
`BPSys1` has 302 (6.9%) missing values	`BPSys1` has 96 (7.2%) missing values	Missing
`BPDia1` has 302 (6.9%) missing values	`BPDia1` has 96 (7.2%) missing values	Missing
`BPSys2` has 244 (5.6%) missing values	`BPSys2` has 85 (6.3%) missing values	Missing
`BPDia2` has 244 (5.6%) missing values	`BPDia2` has 85 (6.3%) missing values	Missing
`BPSys3` has 223 (5.1%) missing values	`BPSys3` has 79 (5.9%) missing values	Missing
`BPDia3` has 223 (5.1%) missing values	`BPDia3` has 79 (5.9%) missing values	Missing
`Testosterone` has 2208 (50.6%) missing values	`Testosterone` has 795 (59.4%) missing values	Missing
`DirectChol` has 209 (4.8%) missing values	`DirectChol` has 99 (7.4%) missing values	Missing
`TotChol` has 209 (4.8%) missing values	`TotChol` has 99 (7.4%) missing values	Missing
`UrineFlow1` has 241 (5.5%) missing values	`UrineFlow1` has 107 (8.0%) missing values	Missing
`UrineVol2` has 3634 (83.3%) missing values	`UrineVol2` has 1192 (89.0%) missing values	Missing
`UrineFlow2` has 3636 (83.3%) missing values	`UrineFlow2` has 1192 (89.0%) missing values	Missing
`DiabetesAge` has 4073 (93.3%) missing values	`DiabetesAge` has 1163 (86.9%) missing values	Missing
`HealthGen` has 420 (9.6%) missing values	`HealthGen` has 190 (14.2%) missing values	Missing
`DaysPhysHlthBad` has 421 (9.6%) missing values	`DaysPhysHlthBad` has 194 (14.5%) missing values	Missing
`DaysMentHlthBad` has 421 (9.6%) missing values	`DaysMentHlthBad` has 192 (14.3%) missing values	Missing
`LittleInterest` has 3541 (81.1%) missing values	`LittleInterest` has 1010 (75.4%) missing values	Missing
`Depressed` has 3637 (83.3%) missing values	`Depressed` has 1013 (75.7%) missing values	Missing
`nPregnancies` has 2812 (64.4%) missing values	`nPregnancies` has 887 (66.2%) missing values	Missing
`nBabies` has 2945 (67.5%) missing values	`nBabies` has 909 (67.9%) missing values	Missing
`Age1stBaby` has 3295 (75.5%) missing values	`Age1stBaby` has 972 (72.6%) missing values	Missing
`PhysActiveDays` has 1951 (44.7%) missing values	`PhysActiveDays` has 821 (61.3%) missing values	Missing
`TVHrsDay` has 2078 (47.6%) missing values	`TVHrsDay` has 723 (54.0%) missing values	Missing
`CompHrsDay` has 2077 (47.6%) missing values	`CompHrsDay` has 722 (53.9%) missing values	Missing
`TVHrsDayChild` has 4365 (100.0%) missing values	`TVHrsDayChild` has 1339 (100.0%) missing values	Missing
`CompHrsDayChild` has 4365 (100.0%) missing values	`CompHrsDayChild` has 1339 (100.0%) missing values	Missing
`Alcohol12PlusYr` has 423 (9.7%) missing values	`Alcohol12PlusYr` has 199 (14.9%) missing values	Missing
`AlcoholDay` has 1208 (27.7%) missing values	`AlcoholDay` has 626 (46.8%) missing values	Missing
`AlcoholYear` has 733 (16.8%) missing values	`AlcoholYear` has 355 (26.5%) missing values	Missing
`SmokeNow` has 2653 (60.8%) missing values	`SmokeNow` has 596 (44.5%) missing values	Missing
`SmokeAge` has 2744 (62.9%) missing values	`SmokeAge` has 613 (45.8%) missing values	Missing
`Marijuana` has 1374 (31.5%) missing values	`Marijuana` has 602 (45.0%) missing values	Missing
`AgeFirstMarij` has 2568 (58.8%) missing values	`AgeFirstMarij` has 956 (71.4%) missing values	Missing
`RegularMarij` has 1374 (31.5%) missing values	`RegularMarij` has 602 (45.0%) missing values	Missing
`AgeRegMarij` has 3641 (83.4%) missing values	`AgeRegMarij` has 1092 (81.6%) missing values	Missing
`HardDrugs` has 835 (19.1%) missing values	`HardDrugs` has 484 (36.1%) missing values	Missing
`SexEver` has 837 (19.2%) missing values	`SexEver` has 480 (35.8%) missing values	Missing
`SexAge` has 959 (22.0%) missing values	`SexAge` has 520 (38.8%) missing values	Missing
`SexNumPartnLife` has 852 (19.5%) missing values	`SexNumPartnLife` has 501 (37.4%) missing values	Missing
`SexNumPartYear` has 1382 (31.7%) missing values	`SexNumPartYear` has 607 (45.3%) missing values	Missing
`SameSex` has 835 (19.1%) missing values	`SameSex` has 481 (35.9%) missing values	Missing
`SexOrientation` has 1406 (32.2%) missing values	`SexOrientation` has 646 (48.2%) missing values	Missing
`Length` is an unsupported type, check if it needs cleaning or further analysis	`Length` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`HeadCirc` is an unsupported type, check if it needs cleaning or further analysis	`HeadCirc` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`BMICatUnder20yrs` is an unsupported type, check if it needs cleaning or further analysis	`BMICatUnder20yrs` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`TVHrsDayChild` is an unsupported type, check if it needs cleaning or further analysis	`TVHrsDayChild` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`CompHrsDayChild` is an unsupported type, check if it needs cleaning or further analysis	`CompHrsDayChild` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`DaysPhysHlthBad` has 2614 (59.9%) zeros	`DaysPhysHlthBad` has 704 (52.6%) zeros	Zeros
`DaysMentHlthBad` has 2269 (52.0%) zeros	`DaysMentHlthBad` has 663 (49.5%) zeros	Zeros
`AlcoholYear` has 473 (10.8%) zeros	`AlcoholYear` has 270 (20.2%) zeros	Zeros
`SexNumPartnLife` has 139 (3.2%) zeros	`SexNumPartnLife` has 45 (3.4%) zeros	Zeros
`SexNumPartYear` has 518 (11.9%) zeros	`SexNumPartYear` has 133 (9.9%) zeros	Zeros
Alert not present in this dataset	`HomeRooms` has 16 (1.2%) missing values	Missing
Alert not present in this dataset	`HomeOwn` has 14 (1.0%) missing values	Missing
Alert not present in this dataset	`BMI` has 14 (1.0%) missing values	Missing
Alert not present in this dataset	`UrineVol1` has 32 (2.4%) missing values	Missing
Alert not present in this dataset	`Poverty` has 14 (1.0%) zeros	Zeros
Alert not present in this dataset	`BPDia3` has 14 (1.0%) zeros	Zeros

Reproduction

	Dataset A	Dataset B
Analysis started	2025-08-31 00:31:04.591042	2025-08-31 00:31:04.933906
Analysis finished	2025-08-31 00:31:04.926789	2025-08-31 00:31:05.222961
Duration	0.34 seconds	0.29 seconds
Software version	ydata-profiling vv4.16.1	ydata-profiling vv4.16.1
Download configuration	config.json	config.json

ID
Real number (ℝ)

	Dataset A	Dataset B
Distinct	2669	983
Distinct (%)	61.1%	73.4%
Missing	0	0
Missing (%)	0.0%	0.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	62238.74296	61474.35474

	Dataset A	Dataset B
Minimum	51630	51657
Maximum	71915	71909
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	51630	51657
5-th percentile	52618.4	52254.3
Q1	57305	56455.5
median	62575	61444
Q3	67392	66614.5
95-th percentile	70984	70896.2
Maximum	71915	71909
Range	20285	20252
Interquartile range (IQR)	10087	10159

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	5863.839644	5982.731972
Coefficient of variation (CV)	0.09421526474	0.09732077705
Kurtosis	-1.179869659	-1.189225533
Mean	62238.74296	61474.35474
Median Absolute Deviation (MAD)	5019	5070
Skewness	-0.1200069753	0.05963696675
Sum	271672113	82314161
Variance	34384615.38	35793081.85
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
62927	7	0.2%
69626	7	0.2%
63297	7	0.2%
63390	6	0.1%
63744	6	0.1%
68035	6	0.1%
60566	6	0.1%
64675	6	0.1%
70653	6	0.1%
63330	6	0.1%
Other values (2659)	4302	98.6%

Value	Count	Frequency (%)
63163	6	0.4%
64530	6	0.4%
53369	5	0.4%
63942	5	0.4%
69637	5	0.4%
70581	4	0.3%
60154	4	0.3%
69365	4	0.3%
61836	4	0.3%
62418	4	0.3%
Other values (973)	1292	96.5%

Value	Count	Frequency (%)
51630	1	< 0.1%
51647	3	0.1%
51654	1	< 0.1%
51656	1	< 0.1%
51667	1	< 0.1%

Value	Count	Frequency (%)
51657	1	0.1%
51701	1	0.1%
51702	2	0.1%
51707	1	0.1%
51711	2	0.1%

Value	Count	Frequency (%)
51657	1	< 0.1%
51701	1	< 0.1%
51702	2	< 0.1%
51707	1	< 0.1%
51711	2	< 0.1%

Value	Count	Frequency (%)
51630	1	0.1%
51647	3	0.2%
51654	1	0.1%
51656	1	0.1%
51667	1	0.1%

Gender
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	6	6
Median length	6	4
Mean length	5.052004582	4.912621359
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	22.052	6.578
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	female	male
2nd row	male	female
3rd row	female	male
4th row	male	female
5th row	male	male

Value	Count	Frequency (%)
female	2296	52.6%
male	2069	47.4%

Value	Count	Frequency (%)
male	728	54.4%
female	611	45.6%

Most occurring characters

Value	Count	Frequency (%)
e	6661	30.2%
m	4365	19.8%
a	4365	19.8%
l	4365	19.8%
f	2296	10.4%

Value	Count	Frequency (%)
e	1950	29.6%
m	1339	20.4%
a	1339	20.4%
l	1339	20.4%
f	611	9.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	22052	100.0%

Value	Count	Frequency (%)
(unknown)	6578	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	6661	30.2%
m	4365	19.8%
a	4365	19.8%
l	4365	19.8%
f	2296	10.4%

Value	Count	Frequency (%)
e	1950	29.6%
m	1339	20.4%
a	1339	20.4%
l	1339	20.4%
f	611	9.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	22052	100.0%

Value	Count	Frequency (%)
(unknown)	6578	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	6661	30.2%
m	4365	19.8%
a	4365	19.8%
l	4365	19.8%
f	2296	10.4%

Value	Count	Frequency (%)
e	1950	29.6%
m	1339	20.4%
a	1339	20.4%
l	1339	20.4%
f	611	9.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	22052	100.0%

Value	Count	Frequency (%)
(unknown)	6578	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	6661	30.2%
m	4365	19.8%
a	4365	19.8%
l	4365	19.8%
f	2296	10.4%

Value	Count	Frequency (%)
e	1950	29.6%
m	1339	20.4%
a	1339	20.4%
l	1339	20.4%
f	611	9.3%

Age
Real number (ℝ)

	Dataset A	Dataset B
Distinct	61	61
Distinct (%)	1.4%	4.6%
Missing	0	0
Missing (%)	0.0%	0.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	46.11065292	50.21135176

	Dataset A	Dataset B
Minimum	20	20
Maximum	80	80
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	20	20
5-th percentile	22	23
Q1	33	36
median	45	49
Q3	58	65
95-th percentile	75	80
Maximum	80	80
Range	60	60
Interquartile range (IQR)	25	29

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	16.20067466	17.90815272
Coefficient of variation (CV)	0.3513434236	0.3566554592
Kurtosis	-0.8495956025	-1.10651191
Mean	46.11065292	50.21135176
Median Absolute Deviation (MAD)	13	14
Skewness	0.2916869443	0.1344584573
Sum	201273	67233
Variance	262.4618594	320.7019338
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
80	137	3.1%
39	122	2.8%
50	107	2.5%
38	103	2.4%
43	102	2.3%
36	101	2.3%
56	100	2.3%
54	99	2.3%
24	98	2.2%
33	95	2.2%
Other values (51)	3301	75.6%

Value	Count	Frequency (%)
80	107	8.0%
40	33	2.5%
30	33	2.5%
42	31	2.3%
48	31	2.3%
39	31	2.3%
46	30	2.2%
63	30	2.2%
51	30	2.2%
45	28	2.1%
Other values (51)	955	71.3%

Value	Count	Frequency (%)
20	81	1.9%
21	72	1.6%
22	74	1.7%
23	73	1.7%
24	98	2.2%

Value	Count	Frequency (%)
20	19	1.4%
21	22	1.6%
22	17	1.3%
23	15	1.1%
24	17	1.3%

Value	Count	Frequency (%)
20	19	0.4%
21	22	0.5%
22	17	0.4%
23	15	0.3%
24	17	0.4%

Value	Count	Frequency (%)
20	81	6.0%
21	72	5.4%
22	74	5.5%
23	73	5.5%
24	98	7.3%

AgeDecade
['Text', 'Text']

	Dataset A	Dataset B
Distinct	6	6
Distinct (%)	0.1%	0.5%
Missing	137	107
Missing (%)	3.1%	8.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	6	6
Median length	6	6
Mean length	5.864238411	5.743506494
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	24.794	7.076
Distinct characters	11	11
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	20-29	30-39
2nd row	60-69	40-49
3rd row	70+	70+
4th row	40-49	50-59
5th row	50-59	60-69

Value	Count	Frequency (%)
30-39	899	21.3%
40-49	836	19.8%
20-29	830	19.6%
50-59	803	19.0%
60-69	573	13.6%
70	287	6.8%

Value	Count	Frequency (%)
40-49	256	20.8%
50-59	230	18.7%
30-39	215	17.5%
20-29	209	17.0%
60-69	164	13.3%
70	158	12.8%

Most occurring characters

Value	Count	Frequency (%)
	4228	17.1%
0	4228	17.1%
-	3941	15.9%
9	3941	15.9%
3	1798	7.3%
4	1672	6.7%
2	1660	6.7%
5	1606	6.5%
6	1146	4.6%
7	287	1.2%

Value	Count	Frequency (%)
	1232	17.4%
0	1232	17.4%
-	1074	15.2%
9	1074	15.2%
4	512	7.2%
5	460	6.5%
3	430	6.1%
2	418	5.9%
6	328	4.6%
7	158	2.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	24794	100.0%

Value	Count	Frequency (%)
(unknown)	7076	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	4228	17.1%
0	4228	17.1%
-	3941	15.9%
9	3941	15.9%
3	1798	7.3%
4	1672	6.7%
2	1660	6.7%
5	1606	6.5%
6	1146	4.6%
7	287	1.2%

Value	Count	Frequency (%)
	1232	17.4%
0	1232	17.4%
-	1074	15.2%
9	1074	15.2%
4	512	7.2%
5	460	6.5%
3	430	6.1%
2	418	5.9%
6	328	4.6%
7	158	2.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	24794	100.0%

Value	Count	Frequency (%)
(unknown)	7076	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	4228	17.1%
0	4228	17.1%
-	3941	15.9%
9	3941	15.9%
3	1798	7.3%
4	1672	6.7%
2	1660	6.7%
5	1606	6.5%
6	1146	4.6%
7	287	1.2%

Value	Count	Frequency (%)
	1232	17.4%
0	1232	17.4%
-	1074	15.2%
9	1074	15.2%
4	512	7.2%
5	460	6.5%
3	430	6.1%
2	418	5.9%
6	328	4.6%
7	158	2.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	24794	100.0%

Value	Count	Frequency (%)
(unknown)	7076	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	4228	17.1%
0	4228	17.1%
-	3941	15.9%
9	3941	15.9%
3	1798	7.3%
4	1672	6.7%
2	1660	6.7%
5	1606	6.5%
6	1146	4.6%
7	287	1.2%

Value	Count	Frequency (%)
	1232	17.4%
0	1232	17.4%
-	1074	15.2%
9	1074	15.2%
4	512	7.2%
5	460	6.5%
3	430	6.1%
2	418	5.9%
6	328	4.6%
7	158	2.2%

AgeMonths
Real number (ℝ)

	Dataset A	Dataset B
Distinct	579	358
Distinct (%)	28.8%	53.2%
Missing	2358	666
Missing (%)	54.0%	49.7%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	544.8325859	569.8528975

	Dataset A	Dataset B
Minimum	240	240
Maximum	955	958
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	240	240
5-th percentile	276	269.6
Q1	401.5	383
median	529	560
Q3	675	729
95-th percentile	867	901.4
Maximum	955	958
Range	715	718
Interquartile range (IQR)	273.5	346

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	179.2621297	201.2157263
Coefficient of variation (CV)	0.3290224086	0.3531011726
Kurtosis	-0.8283895594	-1.09201729
Mean	544.8325859	569.8528975
Median Absolute Deviation (MAD)	139	173
Skewness	0.2773777624	0.1494733196
Sum	1093479	383511
Variance	32134.91114	40487.76851
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
532	16	0.4%
474	15	0.3%
498	14	0.3%
464	13	0.3%
614	13	0.3%
313	13	0.3%
480	12	0.3%
478	12	0.3%
439	12	0.3%
469	11	0.3%
Other values (569)	1876	43.0%
(Missing)	2358	54.0%

Value	Count	Frequency (%)
471	8	0.6%
924	7	0.5%
560	7	0.5%
357	6	0.4%
348	6	0.4%
513	5	0.4%
891	5	0.4%
892	5	0.4%
800	5	0.4%
718	5	0.4%
Other values (348)	614	45.9%
(Missing)	666	49.7%

Value	Count	Frequency (%)
240	3	0.1%
241	5	0.1%
242	5	0.1%
243	3	0.1%
244	2	< 0.1%

Value	Count	Frequency (%)
240	1	0.1%
241	2	0.1%
242	2	0.1%
243	2	0.1%
246	2	0.1%

Value	Count	Frequency (%)
240	1	< 0.1%
241	2	< 0.1%
242	2	< 0.1%
243	2	< 0.1%
246	2	< 0.1%

Value	Count	Frequency (%)
240	3	0.2%
241	5	0.4%
242	5	0.4%
243	3	0.2%
244	2	0.1%

Race1
['Text', 'Text']

	Dataset A	Dataset B
Distinct	5	5
Distinct (%)	0.1%	0.4%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	8	8
Median length	5	5
Mean length	5.204352806	5.781926811
Min length	5	5

Characters and Unicode

	Dataset A	Dataset B
Total characters	22.717	7.742
Distinct characters	18	18
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	White	White
2nd row	Other	White
3rd row	White	Mexican
4th row	White	White
5th row	White	Mexican

Value	Count	Frequency (%)
white	3188	73.0%
black	422	9.7%
other	403	9.2%
hispanic	188	4.3%
mexican	164	3.8%

Value	Count	Frequency (%)
white	622	46.5%
mexican	315	23.5%
black	178	13.3%
hispanic	139	10.4%
other	85	6.3%

Most occurring characters

Value	Count	Frequency (%)
e	3755	16.5%
i	3728	16.4%
t	3591	15.8%
h	3591	15.8%
W	3188	14.0%
a	774	3.4%
c	774	3.4%
k	422	1.9%
l	422	1.9%
B	422	1.9%
Other values (8)	2050	9.0%

Value	Count	Frequency (%)
i	1215	15.7%
e	1022	13.2%
t	707	9.1%
h	707	9.1%
c	632	8.2%
a	632	8.2%
W	622	8.0%
n	454	5.9%
x	315	4.1%
M	315	4.1%
Other values (8)	1121	14.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	22717	100.0%

Value	Count	Frequency (%)
(unknown)	7742	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	3755	16.5%
i	3728	16.4%
t	3591	15.8%
h	3591	15.8%
W	3188	14.0%
a	774	3.4%
c	774	3.4%
k	422	1.9%
l	422	1.9%
B	422	1.9%
Other values (8)	2050	9.0%

Value	Count	Frequency (%)
i	1215	15.7%
e	1022	13.2%
t	707	9.1%
h	707	9.1%
c	632	8.2%
a	632	8.2%
W	622	8.0%
n	454	5.9%
x	315	4.1%
M	315	4.1%
Other values (8)	1121	14.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	22717	100.0%

Value	Count	Frequency (%)
(unknown)	7742	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	3755	16.5%
i	3728	16.4%
t	3591	15.8%
h	3591	15.8%
W	3188	14.0%
a	774	3.4%
c	774	3.4%
k	422	1.9%
l	422	1.9%
B	422	1.9%
Other values (8)	2050	9.0%

Value	Count	Frequency (%)
i	1215	15.7%
e	1022	13.2%
t	707	9.1%
h	707	9.1%
c	632	8.2%
a	632	8.2%
W	622	8.0%
n	454	5.9%
x	315	4.1%
M	315	4.1%
Other values (8)	1121	14.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	22717	100.0%

Value	Count	Frequency (%)
(unknown)	7742	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	3755	16.5%
i	3728	16.4%
t	3591	15.8%
h	3591	15.8%
W	3188	14.0%
a	774	3.4%
c	774	3.4%
k	422	1.9%
l	422	1.9%
B	422	1.9%
Other values (8)	2050	9.0%

Value	Count	Frequency (%)
i	1215	15.7%
e	1022	13.2%
t	707	9.1%
h	707	9.1%
c	632	8.2%
a	632	8.2%
W	622	8.0%
n	454	5.9%
x	315	4.1%
M	315	4.1%
Other values (8)	1121	14.5%

Race3
['Text', 'Text']

	Dataset A	Dataset B
Distinct	6	6
Distinct (%)	0.3%	1.0%
Missing	2077	722
Missing (%)	47.6%	53.9%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	8	8
Median length	5	5
Mean length	5.181381119	5.858995138
Min length	5	5

Characters and Unicode

	Dataset A	Dataset B
Total characters	11.855	3.615
Distinct characters	19	19
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	White	White
2nd row	White	White
3rd row	White	Black
4th row	Black	Black
5th row	White	White

Value	Count	Frequency (%)
white	1669	72.9%
black	228	10.0%
asian	166	7.3%
hispanic	87	3.8%
mexican	77	3.4%
other	61	2.7%

Value	Count	Frequency (%)
white	282	45.7%
mexican	133	21.6%
hispanic	88	14.3%
black	74	12.0%
asian	28	4.5%
other	12	1.9%

Most occurring characters

Value	Count	Frequency (%)
i	2086	17.6%
e	1807	15.2%
h	1730	14.6%
t	1730	14.6%
W	1669	14.1%
a	558	4.7%
c	392	3.3%
n	330	2.8%
s	253	2.1%
k	228	1.9%
Other values (9)	1072	9.0%

Value	Count	Frequency (%)
i	619	17.1%
e	427	11.8%
a	323	8.9%
c	295	8.2%
t	294	8.1%
h	294	8.1%
W	282	7.8%
n	249	6.9%
x	133	3.7%
M	133	3.7%
Other values (9)	566	15.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11855	100.0%

Value	Count	Frequency (%)
(unknown)	3615	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	2086	17.6%
e	1807	15.2%
h	1730	14.6%
t	1730	14.6%
W	1669	14.1%
a	558	4.7%
c	392	3.3%
n	330	2.8%
s	253	2.1%
k	228	1.9%
Other values (9)	1072	9.0%

Value	Count	Frequency (%)
i	619	17.1%
e	427	11.8%
a	323	8.9%
c	295	8.2%
t	294	8.1%
h	294	8.1%
W	282	7.8%
n	249	6.9%
x	133	3.7%
M	133	3.7%
Other values (9)	566	15.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11855	100.0%

Value	Count	Frequency (%)
(unknown)	3615	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	2086	17.6%
e	1807	15.2%
h	1730	14.6%
t	1730	14.6%
W	1669	14.1%
a	558	4.7%
c	392	3.3%
n	330	2.8%
s	253	2.1%
k	228	1.9%
Other values (9)	1072	9.0%

Value	Count	Frequency (%)
i	619	17.1%
e	427	11.8%
a	323	8.9%
c	295	8.2%
t	294	8.1%
h	294	8.1%
W	282	7.8%
n	249	6.9%
x	133	3.7%
M	133	3.7%
Other values (9)	566	15.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11855	100.0%

Value	Count	Frequency (%)
(unknown)	3615	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	2086	17.6%
e	1807	15.2%
h	1730	14.6%
t	1730	14.6%
W	1669	14.1%
a	558	4.7%
c	392	3.3%
n	330	2.8%
s	253	2.1%
k	228	1.9%
Other values (9)	1072	9.0%

Value	Count	Frequency (%)
i	619	17.1%
e	427	11.8%
a	323	8.9%
c	295	8.2%
t	294	8.1%
h	294	8.1%
W	282	7.8%
n	249	6.9%
x	133	3.7%
M	133	3.7%
Other values (9)	566	15.7%

Education
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	11	11
Median length	11	11
Mean length	11	9.989544436
Min length	11	8

Characters and Unicode

	Dataset A	Dataset B
Total characters	48.015	13.376
Distinct characters	11	11
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	CollegeGrad	8thGrade
2nd row	SomeCollege	8thGrade
3rd row	CollegeGrad	8thGrade
4th row	SomeCollege	8thGrade
5th row	SomeCollege	9_11thGrade

Value	Count	Frequency (%)
somecollege	2267	51.9%
collegegrad	2098	48.1%

Value	Count	Frequency (%)
9_11thgrade	888	66.3%
8thgrade	451	33.7%

Most occurring characters

Value	Count	Frequency (%)
e	10997	22.9%
l	8730	18.2%
o	6632	13.8%
C	4365	9.1%
g	4365	9.1%
S	2267	4.7%
m	2267	4.7%
G	2098	4.4%
r	2098	4.4%
a	2098	4.4%

Value	Count	Frequency (%)
1	1776	13.3%
t	1339	10.0%
h	1339	10.0%
G	1339	10.0%
r	1339	10.0%
a	1339	10.0%
d	1339	10.0%
e	1339	10.0%
9	888	6.6%
_	888	6.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	48015	100.0%

Value	Count	Frequency (%)
(unknown)	13376	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	10997	22.9%
l	8730	18.2%
o	6632	13.8%
C	4365	9.1%
g	4365	9.1%
S	2267	4.7%
m	2267	4.7%
G	2098	4.4%
r	2098	4.4%
a	2098	4.4%

Value	Count	Frequency (%)
1	1776	13.3%
t	1339	10.0%
h	1339	10.0%
G	1339	10.0%
r	1339	10.0%
a	1339	10.0%
d	1339	10.0%
e	1339	10.0%
9	888	6.6%
_	888	6.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	48015	100.0%

Value	Count	Frequency (%)
(unknown)	13376	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	10997	22.9%
l	8730	18.2%
o	6632	13.8%
C	4365	9.1%
g	4365	9.1%
S	2267	4.7%
m	2267	4.7%
G	2098	4.4%
r	2098	4.4%
a	2098	4.4%

Value	Count	Frequency (%)
1	1776	13.3%
t	1339	10.0%
h	1339	10.0%
G	1339	10.0%
r	1339	10.0%
a	1339	10.0%
d	1339	10.0%
e	1339	10.0%
9	888	6.6%
_	888	6.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	48015	100.0%

Value	Count	Frequency (%)
(unknown)	13376	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	10997	22.9%
l	8730	18.2%
o	6632	13.8%
C	4365	9.1%
g	4365	9.1%
S	2267	4.7%
m	2267	4.7%
G	2098	4.4%
r	2098	4.4%
a	2098	4.4%

Value	Count	Frequency (%)
1	1776	13.3%
t	1339	10.0%
h	1339	10.0%
G	1339	10.0%
r	1339	10.0%
a	1339	10.0%
d	1339	10.0%
e	1339	10.0%
9	888	6.6%
_	888	6.6%

MaritalStatus
['Text', 'Text']

	Dataset A	Dataset B
Distinct	6	6
Distinct (%)	0.1%	0.4%
Missing	3	0
Missing (%)	0.1%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	12	12
Median length	7	7
Mean length	8.375515818	8.412247946
Min length	7	7

Characters and Unicode

	Dataset A	Dataset B
Total characters	36.534	11.264
Distinct characters	19	19
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Married	Married
2nd row	Married	Married
3rd row	Married	Married
4th row	Married	Widowed
5th row	Married	Married

Value	Count	Frequency (%)
married	2522	57.8%
nevermarried	864	19.8%
divorced	418	9.6%
livepartner	272	6.2%
widowed	199	4.6%
separated	87	2.0%

Value	Count	Frequency (%)
married	647	48.3%
nevermarried	211	15.8%
widowed	156	11.7%
livepartner	151	11.3%
divorced	116	8.7%
separated	58	4.3%

Most occurring characters

Value	Count	Frequency (%)
r	8685	23.8%
e	6449	17.7%
d	4289	11.7%
i	4275	11.7%
a	3832	10.5%
M	3386	9.3%
v	1554	4.3%
N	864	2.4%
o	617	1.7%
D	418	1.1%
Other values (9)	2165	5.9%

Value	Count	Frequency (%)
r	2403	21.3%
e	1970	17.5%
d	1344	11.9%
i	1281	11.4%
a	1125	10.0%
M	858	7.6%
v	478	4.2%
o	272	2.4%
N	211	1.9%
t	209	1.9%
Other values (9)	1113	9.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	36534	100.0%

Value	Count	Frequency (%)
(unknown)	11264	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	8685	23.8%
e	6449	17.7%
d	4289	11.7%
i	4275	11.7%
a	3832	10.5%
M	3386	9.3%
v	1554	4.3%
N	864	2.4%
o	617	1.7%
D	418	1.1%
Other values (9)	2165	5.9%

Value	Count	Frequency (%)
r	2403	21.3%
e	1970	17.5%
d	1344	11.9%
i	1281	11.4%
a	1125	10.0%
M	858	7.6%
v	478	4.2%
o	272	2.4%
N	211	1.9%
t	209	1.9%
Other values (9)	1113	9.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	36534	100.0%

Value	Count	Frequency (%)
(unknown)	11264	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	8685	23.8%
e	6449	17.7%
d	4289	11.7%
i	4275	11.7%
a	3832	10.5%
M	3386	9.3%
v	1554	4.3%
N	864	2.4%
o	617	1.7%
D	418	1.1%
Other values (9)	2165	5.9%

Value	Count	Frequency (%)
r	2403	21.3%
e	1970	17.5%
d	1344	11.9%
i	1281	11.4%
a	1125	10.0%
M	858	7.6%
v	478	4.2%
o	272	2.4%
N	211	1.9%
t	209	1.9%
Other values (9)	1113	9.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	36534	100.0%

Value	Count	Frequency (%)
(unknown)	11264	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	8685	23.8%
e	6449	17.7%
d	4289	11.7%
i	4275	11.7%
a	3832	10.5%
M	3386	9.3%
v	1554	4.3%
N	864	2.4%
o	617	1.7%
D	418	1.1%
Other values (9)	2165	5.9%

Value	Count	Frequency (%)
r	2403	21.3%
e	1970	17.5%
d	1344	11.9%
i	1281	11.4%
a	1125	10.0%
M	858	7.6%
v	478	4.2%
o	272	2.4%
N	211	1.9%
t	209	1.9%
Other values (9)	1113	9.9%

HHIncome
['Text', 'Text']

	Dataset A	Dataset B
Distinct	12	12
Distinct (%)	0.3%	1.0%
Missing	301	173
Missing (%)	6.9%	12.9%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	11	11
Median length	11	11
Mean length	10.60826772	10.71012007
Min length	7	7

Characters and Unicode

	Dataset A	Dataset B
Total characters	43.112	12.488
Distinct characters	15	15
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	more 99999	20000-24999
2nd row	10000-14999	15000-19999
3rd row	75000-99999	65000-74999
4th row	35000-44999	65000-74999
5th row	75000-99999	5000-9999

Value	Count	Frequency (%)
more	1357	25.0%
99999	1357	25.0%
75000-99999	604	11.1%
45000-54999	350	6.5%
25000-34999	341	6.3%
35000-44999	319	5.9%
65000-74999	282	5.2%
55000-64999	275	5.1%
20000-24999	160	3.0%
10000-14999	142	2.6%
Other values (3)	234	4.3%

Value	Count	Frequency (%)
25000-34999	186	15.1%
15000-19999	143	11.6%
20000-24999	136	11.0%
10000-14999	127	10.3%
35000-44999	119	9.6%
45000-54999	76	6.2%
75000-99999	71	5.8%
5000-9999	70	5.7%
more	68	5.5%
99999	68	5.5%
Other values (3)	170	13.8%

Most occurring characters

Value	Count	Frequency (%)
9	16302	37.8%
0	8331	19.3%
5	2984	6.9%
-	2707	6.3%
4	2584	6.0%
	1454	3.4%
m	1357	3.1%
o	1357	3.1%
r	1357	3.1%
e	1357	3.1%
Other values (5)	3322	7.7%

Value	Count	Frequency (%)
9	3989	31.9%
0	3457	27.7%
-	1098	8.8%
4	1009	8.1%
5	928	7.4%
1	540	4.3%
2	458	3.7%
3	305	2.4%
	188	1.5%
7	124	1.0%
Other values (5)	392	3.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	43112	100.0%

Value	Count	Frequency (%)
(unknown)	12488	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
9	16302	37.8%
0	8331	19.3%
5	2984	6.9%
-	2707	6.3%
4	2584	6.0%
	1454	3.4%
m	1357	3.1%
o	1357	3.1%
r	1357	3.1%
e	1357	3.1%
Other values (5)	3322	7.7%

Value	Count	Frequency (%)
9	3989	31.9%
0	3457	27.7%
-	1098	8.8%
4	1009	8.1%
5	928	7.4%
1	540	4.3%
2	458	3.7%
3	305	2.4%
	188	1.5%
7	124	1.0%
Other values (5)	392	3.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	43112	100.0%

Value	Count	Frequency (%)
(unknown)	12488	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
9	16302	37.8%
0	8331	19.3%
5	2984	6.9%
-	2707	6.3%
4	2584	6.0%
	1454	3.4%
m	1357	3.1%
o	1357	3.1%
r	1357	3.1%
e	1357	3.1%
Other values (5)	3322	7.7%

Value	Count	Frequency (%)
9	3989	31.9%
0	3457	27.7%
-	1098	8.8%
4	1009	8.1%
5	928	7.4%
1	540	4.3%
2	458	3.7%
3	305	2.4%
	188	1.5%
7	124	1.0%
Other values (5)	392	3.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	43112	100.0%

Value	Count	Frequency (%)
(unknown)	12488	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
9	16302	37.8%
0	8331	19.3%
5	2984	6.9%
-	2707	6.3%
4	2584	6.0%
	1454	3.4%
m	1357	3.1%
o	1357	3.1%
r	1357	3.1%
e	1357	3.1%
Other values (5)	3322	7.7%

Value	Count	Frequency (%)
9	3989	31.9%
0	3457	27.7%
-	1098	8.8%
4	1009	8.1%
5	928	7.4%
1	540	4.3%
2	458	3.7%
3	305	2.4%
	188	1.5%
7	124	1.0%
Other values (5)	392	3.1%

HHIncomeMid
Real number (ℝ)

	Dataset A	Dataset B
Distinct	12	12
Distinct (%)	0.3%	1.0%
Missing	301	173
Missing (%)	6.9%	12.9%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	67310.5315	36605.91767

	Dataset A	Dataset B
Minimum	2500	2500
Maximum	100000	100000
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	2500	2500
5-th percentile	12500	7500
Q1	40000	17500
median	70000	30000
Q3	100000	50000
95-th percentile	100000	100000
Maximum	100000	100000
Range	97500	97500
Interquartile range (IQR)	60000	32500

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	31353.02749	26957.27297
Coefficient of variation (CV)	0.4657967601	0.736418445
Kurtosis	-1.279221631	0.01258436765
Mean	67310.5315	36605.91767
Median Absolute Deviation (MAD)	30000	12500
Skewness	-0.4146437607	0.9999381321
Sum	273550000	42682500
Variance	983012333.1	726694565.8
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
100000	1357	31.1%
87500	604	13.8%
50000	350	8.0%
30000	341	7.8%
40000	319	7.3%
70000	282	6.5%
60000	275	6.3%
22500	160	3.7%
12500	142	3.3%
17500	137	3.1%
Other values (2)	97	2.2%
(Missing)	301	6.9%

Value	Count	Frequency (%)
30000	186	13.9%
17500	143	10.7%
22500	136	10.2%
12500	127	9.5%
40000	119	8.9%
50000	76	5.7%
87500	71	5.3%
7500	70	5.2%
100000	68	5.1%
60000	67	5.0%
Other values (2)	103	7.7%
(Missing)	173	12.9%

Value	Count	Frequency (%)
2500	46	1.1%
7500	51	1.2%
12500	142	3.3%
17500	137	3.1%
22500	160	3.7%

Value	Count	Frequency (%)
2500	50	3.7%
7500	70	5.2%
12500	127	9.5%
17500	143	10.7%
22500	136	10.2%

Value	Count	Frequency (%)
2500	50	1.1%
7500	70	1.6%
12500	127	2.9%
17500	143	3.3%
22500	136	3.1%

Value	Count	Frequency (%)
2500	46	3.4%
7500	51	3.8%
12500	142	10.6%
17500	137	10.2%
22500	160	11.9%

Poverty
Real number (ℝ)

	Dataset A	Dataset B
Distinct	391	280
Distinct (%)	9.5%	23.6%
Missing	259	154
Missing (%)	5.9%	11.5%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	3.454510472	1.747974684

	Dataset A	Dataset B
Minimum	0	0
Maximum	5	5
Zeros	23	14
Zeros (%)	0.5%	1.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0.72	0.234
Q1	2.03	0.82
median	3.85	1.31
Q3	5	2.45
95-th percentile	5	5
Maximum	5	5
Range	5	5
Interquartile range (IQR)	2.97	1.63

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.576905329	1.3157036
Coefficient of variation (CV)	0.4564772178	0.7527017479
Kurtosis	-1.131187589	0.272914025
Mean	3.454510472	1.747974684
Median Absolute Deviation (MAD)	1.15	0.63
Skewness	-0.5395722861	1.073458618
Sum	14184.22	2071.35
Variance	2.486630418	1.731075962
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5	1442	33.0%
3.51	41	0.9%
3.4	34	0.8%
0.92	32	0.7%
3.43	32	0.7%
2.75	31	0.7%
4.54	31	0.7%
1.31	29	0.7%
3.97	28	0.6%
4.59	27	0.6%
Other values (381)	2379	54.5%
(Missing)	259	5.9%

Value	Count	Frequency (%)
5	62	4.6%
0.81	16	1.2%
1.63	15	1.1%
0.89	14	1.0%
0.82	14	1.0%
0	14	1.0%
1.24	14	1.0%
1.37	14	1.0%
1.11	13	1.0%
1.02	13	1.0%
Other values (270)	996	74.4%
(Missing)	154	11.5%

Value	Count	Frequency (%)
0	23	0.5%
0.01	3	0.1%
0.03	1	< 0.1%
0.04	1	< 0.1%
0.05	2	< 0.1%

Value	Count	Frequency (%)
0	14	1.0%
0.01	3	0.2%
0.02	2	0.1%
0.03	4	0.3%
0.04	2	0.1%

Value	Count	Frequency (%)
0	14	0.3%
0.01	3	0.1%
0.02	2	< 0.1%
0.03	4	0.1%
0.04	2	< 0.1%

Value	Count	Frequency (%)
0	23	1.7%
0.01	3	0.2%
0.03	1	0.1%
0.04	1	0.1%
0.05	2	0.1%

HomeRooms
Real number (ℝ)

	Dataset A	Dataset B
Distinct	13	13
Distinct (%)	0.3%	1.0%
Missing	23	16
Missing (%)	0.5%	1.2%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	6.4866421	5.287981859

	Dataset A	Dataset B
Minimum	1	1
Maximum	13	13
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1	1
5-th percentile	3	3
Q1	5	4
median	6	5
Q3	8	6
95-th percentile	11	9
Maximum	13	13
Range	12	12
Interquartile range (IQR)	3	2

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	2.350370154	1.844827358
Coefficient of variation (CV)	0.3623400394	0.348871726
Kurtosis	-0.07447598025	1.069539551
Mean	6.4866421	5.287981859
Median Absolute Deviation (MAD)	2	1
Skewness	0.344503497	0.7235017307
Sum	28165	6996
Variance	5.524239862	3.403387982
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
7	722	16.5%
6	692	15.9%
5	630	14.4%
4	585	13.4%
8	544	12.5%
9	324	7.4%
3	257	5.9%
10	256	5.9%
11	123	2.8%
13	59	1.4%
Other values (3)	150	3.4%

Value	Count	Frequency (%)
4	309	23.1%
5	293	21.9%
6	237	17.7%
7	166	12.4%
3	143	10.7%
8	63	4.7%
9	35	2.6%
2	26	1.9%
10	17	1.3%
11	16	1.2%
Other values (3)	18	1.3%
(Missing)	16	1.2%

Value	Count	Frequency (%)
1	50	1.1%
2	50	1.1%
3	257	5.9%
4	585	13.4%
5	630	14.4%

Value	Count	Frequency (%)
1	14	1.0%
2	26	1.9%
3	143	10.7%
4	309	23.1%
5	293	21.9%

Value	Count	Frequency (%)
1	14	0.3%
2	26	0.6%
3	143	3.3%
4	309	7.1%
5	293	6.7%

Value	Count	Frequency (%)
1	50	3.7%
2	50	3.7%
3	257	19.2%
4	585	43.7%
5	630	47.1%

HomeOwn
['Text', 'Text']

	Dataset A	Dataset B
Distinct	3	3
Distinct (%)	0.1%	0.2%
Missing	18	14
Missing (%)	0.4%	1.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	5	5
Median length	3	3
Mean length	3.318150449	3.498113208
Min length	3	3

Characters and Unicode

	Dataset A	Dataset B
Total characters	14.424	4.635
Distinct characters	8	8
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Own	Own
2nd row	Own	Rent
3rd row	Own	Own
4th row	Rent	Rent
5th row	Own	Rent

Value	Count	Frequency (%)
own	3063	70.5%
rent	1185	27.3%
other	99	2.3%

Value	Count	Frequency (%)
own	704	53.1%
rent	582	43.9%
other	39	2.9%

Most occurring characters

Value	Count	Frequency (%)
n	4248	29.5%
O	3162	21.9%
w	3063	21.2%
e	1284	8.9%
t	1284	8.9%
R	1185	8.2%
h	99	0.7%
r	99	0.7%

Value	Count	Frequency (%)
n	1286	27.7%
O	743	16.0%
w	704	15.2%
e	621	13.4%
t	621	13.4%
R	582	12.6%
h	39	0.8%
r	39	0.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	14424	100.0%

Value	Count	Frequency (%)
(unknown)	4635	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	4248	29.5%
O	3162	21.9%
w	3063	21.2%
e	1284	8.9%
t	1284	8.9%
R	1185	8.2%
h	99	0.7%
r	99	0.7%

Value	Count	Frequency (%)
n	1286	27.7%
O	743	16.0%
w	704	15.2%
e	621	13.4%
t	621	13.4%
R	582	12.6%
h	39	0.8%
r	39	0.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	14424	100.0%

Value	Count	Frequency (%)
(unknown)	4635	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	4248	29.5%
O	3162	21.9%
w	3063	21.2%
e	1284	8.9%
t	1284	8.9%
R	1185	8.2%
h	99	0.7%
r	99	0.7%

Value	Count	Frequency (%)
n	1286	27.7%
O	743	16.0%
w	704	15.2%
e	621	13.4%
t	621	13.4%
R	582	12.6%
h	39	0.8%
r	39	0.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	14424	100.0%

Value	Count	Frequency (%)
(unknown)	4635	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	4248	29.5%
O	3162	21.9%
w	3063	21.2%
e	1284	8.9%
t	1284	8.9%
R	1185	8.2%
h	99	0.7%
r	99	0.7%

Value	Count	Frequency (%)
n	1286	27.7%
O	743	16.0%
w	704	15.2%
e	621	13.4%
t	621	13.4%
R	582	12.6%
h	39	0.8%
r	39	0.8%

Work
['Text', 'Text']

	Dataset A	Dataset B
Distinct	3	3
Distinct (%)	0.1%	0.2%
Missing	0	1
Missing (%)	0.0%	0.1%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	10	10
Median length	7	10
Mean length	7.870103093	8.540358744
Min length	7	7

Characters and Unicode

	Dataset A	Dataset B
Total characters	34.353	11.427
Distinct characters	10	10
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Working	NotWorking
2nd row	NotWorking	NotWorking
3rd row	NotWorking	Working
4th row	Working	NotWorking
5th row	Working	Working

Value	Count	Frequency (%)
working	2939	67.3%
notworking	1266	29.0%
looking	160	3.7%

Value	Count	Frequency (%)
notworking	687	51.3%
working	599	44.8%
looking	52	3.9%

Most occurring characters

Value	Count	Frequency (%)
o	5791	16.9%
k	4365	12.7%
i	4365	12.7%
n	4365	12.7%
g	4365	12.7%
W	4205	12.2%
r	4205	12.2%
N	1266	3.7%
t	1266	3.7%
L	160	0.5%

Value	Count	Frequency (%)
o	2077	18.2%
k	1338	11.7%
i	1338	11.7%
n	1338	11.7%
g	1338	11.7%
W	1286	11.3%
r	1286	11.3%
N	687	6.0%
t	687	6.0%
L	52	0.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	34353	100.0%

Value	Count	Frequency (%)
(unknown)	11427	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	5791	16.9%
k	4365	12.7%
i	4365	12.7%
n	4365	12.7%
g	4365	12.7%
W	4205	12.2%
r	4205	12.2%
N	1266	3.7%
t	1266	3.7%
L	160	0.5%

Value	Count	Frequency (%)
o	2077	18.2%
k	1338	11.7%
i	1338	11.7%
n	1338	11.7%
g	1338	11.7%
W	1286	11.3%
r	1286	11.3%
N	687	6.0%
t	687	6.0%
L	52	0.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	34353	100.0%

Value	Count	Frequency (%)
(unknown)	11427	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	5791	16.9%
k	4365	12.7%
i	4365	12.7%
n	4365	12.7%
g	4365	12.7%
W	4205	12.2%
r	4205	12.2%
N	1266	3.7%
t	1266	3.7%
L	160	0.5%

Value	Count	Frequency (%)
o	2077	18.2%
k	1338	11.7%
i	1338	11.7%
n	1338	11.7%
g	1338	11.7%
W	1286	11.3%
r	1286	11.3%
N	687	6.0%
t	687	6.0%
L	52	0.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	34353	100.0%

Value	Count	Frequency (%)
(unknown)	11427	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	5791	16.9%
k	4365	12.7%
i	4365	12.7%
n	4365	12.7%
g	4365	12.7%
W	4205	12.2%
r	4205	12.2%
N	1266	3.7%
t	1266	3.7%
L	160	0.5%

Value	Count	Frequency (%)
o	2077	18.2%
k	1338	11.7%
i	1338	11.7%
n	1338	11.7%
g	1338	11.7%
W	1286	11.3%
r	1286	11.3%
N	687	6.0%
t	687	6.0%
L	52	0.5%

Weight
Real number (ℝ)

	Dataset A	Dataset B
Distinct	798	530
Distinct (%)	18.4%	39.9%
Missing	30	11
Missing (%)	0.7%	0.8%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	82.33997693	80.91731928

	Dataset A	Dataset B
Minimum	39.7	38.5
Maximum	203	223
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	39.7	38.5
5-th percentile	53.1	53.07
Q1	67	66.375
median	79.8	78
Q3	95.2	90.925
95-th percentile	119.33	117.86
Maximum	203	223
Range	163.3	184.5
Interquartile range (IQR)	28.2	24.55

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	20.78435648	21.5063777
Coefficient of variation (CV)	0.2524212085	0.2657821328
Kurtosis	1.156208635	4.380167832
Mean	82.33997693	80.91731928
Median Absolute Deviation (MAD)	13.7	12.4
Skewness	0.8023564927	1.386329681
Sum	356943.8	107458.2
Variance	431.9894744	462.5242816
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
77.3	23	0.5%
90.3	23	0.5%
73.8	21	0.5%
61.7	21	0.5%
65.3	20	0.5%
84.8	20	0.5%
91.1	18	0.4%
61.1	18	0.4%
91.7	17	0.4%
63.3	17	0.4%
Other values (788)	4137	94.8%
(Missing)	30	0.7%

Value	Count	Frequency (%)
64.5	11	0.8%
87.3	11	0.8%
78.1	9	0.7%
79.2	9	0.7%
83.2	9	0.7%
65.1	9	0.7%
99.3	8	0.6%
76	8	0.6%
70.8	8	0.6%
140.1	8	0.6%
Other values (520)	1238	92.5%
(Missing)	11	0.8%

Value	Count	Frequency (%)
39.7	1	< 0.1%
40.2	1	< 0.1%
40.8	1	< 0.1%
41.1	3	0.1%
41.5	1	< 0.1%

Value	Count	Frequency (%)
38.5	1	0.1%
38.7	1	0.1%
39.3	2	0.1%
40.7	3	0.2%
40.8	1	0.1%

Value	Count	Frequency (%)
38.5	1	< 0.1%
38.7	1	< 0.1%
39.3	2	< 0.1%
40.7	3	0.1%
40.8	1	< 0.1%

Value	Count	Frequency (%)
39.7	1	0.1%
40.2	1	0.1%
40.8	1	0.1%
41.1	3	0.2%
41.5	1	0.1%

Length
[None, None]

	Dataset A	Dataset B
Missing	4365	1339
Missing (%)	100.0%	100.0%
Memory size	197.2 KiB	53.2 KiB

HeadCirc
[None, None]

	Dataset A	Dataset B
Missing	4365	1339
Missing (%)	100.0%	100.0%
Memory size	197.2 KiB	53.2 KiB

Height
Real number (ℝ)

	Dataset A	Dataset B
Distinct	458	370
Distinct (%)	10.6%	27.9%
Missing	28	13
Missing (%)	0.6%	1.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	169.9250865	166.0863499

	Dataset A	Dataset B
Minimum	140	134.5
Maximum	199.9	200.4
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	140	134.5
5-th percentile	154.5	149.5
Q1	162.8	157.9
median	169.6	166.2
Q3	176.8	173.6
95-th percentile	186.6	183.4
Maximum	199.9	200.4
Range	59.9	65.9
Interquartile range (IQR)	14	15.7

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	9.778168584	10.50775034
Coefficient of variation (CV)	0.05754399652	0.06326679074
Kurtosis	-0.378252253	-0.5062421774
Mean	169.9250865	166.0863499
Median Absolute Deviation (MAD)	7	7.8
Skewness	0.1232691608	0.06452696498
Sum	736965.1	220230.5
Variance	95.61258086	110.4128173
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
171.9	29	0.7%
173.8	28	0.6%
163.6	28	0.6%
160.7	27	0.6%
160.6	27	0.6%
176.6	27	0.6%
177.1	26	0.6%
166.7	26	0.6%
175.3	26	0.6%
173.2	25	0.6%
Other values (448)	4068	93.2%
(Missing)	28	0.6%

Value	Count	Frequency (%)
173.2	12	0.9%
178.8	11	0.8%
157.9	11	0.8%
173.1	11	0.8%
172.6	11	0.8%
168	11	0.8%
156.7	10	0.7%
163.1	10	0.7%
173	10	0.7%
162.8	10	0.7%
Other values (360)	1219	91.0%
(Missing)	13	1.0%

Value	Count	Frequency (%)
140	1	< 0.1%
141.2	2	< 0.1%
143.1	1	< 0.1%
143.3	1	< 0.1%
143.8	1	< 0.1%

Value	Count	Frequency (%)
134.5	1	0.1%
139.8	1	0.1%
141.3	2	0.1%
143.4	1	0.1%
143.6	1	0.1%

Value	Count	Frequency (%)
134.5	1	< 0.1%
139.8	1	< 0.1%
141.3	2	< 0.1%
143.4	1	< 0.1%
143.6	1	< 0.1%

Value	Count	Frequency (%)
140	1	0.1%
141.2	2	0.1%
143.1	1	0.1%
143.3	1	0.1%
143.8	1	0.1%

BMI
Real number (ℝ)

	Dataset A	Dataset B
Distinct	1198	636
Distinct (%)	27.6%	48.0%
Missing	32	14
Missing (%)	0.7%	1.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	28.41318255	29.25124528

	Dataset A	Dataset B
Minimum	15.02	15.7
Maximum	68.63	67.83
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	15.02	15.7
5-th percentile	20	20.3
Q1	23.8	24.8
median	27.4	28.1
Q3	31.8	32.5
95-th percentile	40.68	41.862
Maximum	68.63	67.83
Range	53.61	52.13
Interquartile range (IQR)	8	7.7

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	6.408522622	6.836315771
Coefficient of variation (CV)	0.2255475116	0.2337102474
Kurtosis	2.192624826	3.536839754
Mean	28.41318255	29.25124528
Median Absolute Deviation (MAD)	4	3.78
Skewness	1.104189255	1.315612394
Sum	123114.32	38757.9
Variance	41.06916219	46.73521333
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
25.6	40	0.9%
22.6	35	0.8%
23.2	31	0.7%
26.4	28	0.6%
24.5	27	0.6%
30.5	27	0.6%
25.2	26	0.6%
22.5	25	0.6%
29.7	25	0.6%
28	24	0.5%
Other values (1188)	4045	92.7%
(Missing)	32	0.7%

Value	Count	Frequency (%)
28.6	15	1.1%
27.8	12	0.9%
32.5	12	0.9%
26.9	11	0.8%
24.7	10	0.7%
26.6	10	0.7%
27.2	10	0.7%
29.4	9	0.7%
28.9	9	0.7%
23.5	8	0.6%
Other values (626)	1219	91.0%
(Missing)	14	1.0%

Value	Count	Frequency (%)
15.02	1	< 0.1%
15.98	1	< 0.1%
16.51	1	< 0.1%
16.6	3	0.1%
16.73	3	0.1%

Value	Count	Frequency (%)
15.7	1	0.1%
15.98	3	0.2%
16.03	1	0.1%
16.38	1	0.1%
17.7	2	0.1%

Value	Count	Frequency (%)
15.7	1	< 0.1%
15.98	3	0.1%
16.03	1	< 0.1%
16.38	1	< 0.1%
17.7	2	< 0.1%

Value	Count	Frequency (%)
15.02	1	0.1%
15.98	1	0.1%
16.51	1	0.1%
16.6	3	0.2%
16.73	3	0.2%

BMICatUnder20yrs
[None, None]

	Dataset A	Dataset B
Missing	4365	1339
Missing (%)	100.0%	100.0%
Memory size	197.2 KiB	53.2 KiB

BMI_WHO
['Text', 'Text']

	Dataset A	Dataset B
Distinct	4	4
Distinct (%)	0.1%	0.3%
Missing	57	18
Missing (%)	1.3%	1.3%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	12	12
Median length	12	12
Mean length	10.90668524	10.83043149
Min length	9	9

Characters and Unicode

	Dataset A	Dataset B
Total characters	46.986	14.307
Distinct characters	16	16
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	18.5_to_24.9	25.0_to_29.9
2nd row	18.5_to_24.9	25.0_to_29.9
3rd row	30.0_plus	30.0_plus
4th row	30.0_plus	25.0_to_29.9
5th row	30.0_plus	25.0_to_29.9

Value	Count	Frequency (%)
30.0_plus	1502	34.9%
25.0_to_29.9	1397	32.4%
18.5_to_24.9	1341	31.1%
12.0_18.5	68	1.6%

Value	Count	Frequency (%)
30.0_plus	493	37.3%
25.0_to_29.9	478	36.2%
18.5_to_24.9	328	24.8%
12.0_18.5	22	1.7%

Most occurring characters

Value	Count	Frequency (%)
.	7114	15.1%
_	7046	15.0%
0	4469	9.5%
2	4203	8.9%
9	4135	8.8%
5	2806	6.0%
t	2738	5.8%
o	2738	5.8%
3	1502	3.2%
p	1502	3.2%
Other values (6)	8733	18.6%

Value	Count	Frequency (%)
.	2149	15.0%
_	2127	14.9%
0	1486	10.4%
2	1306	9.1%
9	1284	9.0%
5	828	5.8%
t	806	5.6%
o	806	5.6%
3	493	3.4%
p	493	3.4%
Other values (6)	2529	17.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	46986	100.0%

Value	Count	Frequency (%)
(unknown)	14307	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	7114	15.1%
_	7046	15.0%
0	4469	9.5%
2	4203	8.9%
9	4135	8.8%
5	2806	6.0%
t	2738	5.8%
o	2738	5.8%
3	1502	3.2%
p	1502	3.2%
Other values (6)	8733	18.6%

Value	Count	Frequency (%)
.	2149	15.0%
_	2127	14.9%
0	1486	10.4%
2	1306	9.1%
9	1284	9.0%
5	828	5.8%
t	806	5.6%
o	806	5.6%
3	493	3.4%
p	493	3.4%
Other values (6)	2529	17.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	46986	100.0%

Value	Count	Frequency (%)
(unknown)	14307	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	7114	15.1%
_	7046	15.0%
0	4469	9.5%
2	4203	8.9%
9	4135	8.8%
5	2806	6.0%
t	2738	5.8%
o	2738	5.8%
3	1502	3.2%
p	1502	3.2%
Other values (6)	8733	18.6%

Value	Count	Frequency (%)
.	2149	15.0%
_	2127	14.9%
0	1486	10.4%
2	1306	9.1%
9	1284	9.0%
5	828	5.8%
t	806	5.6%
o	806	5.6%
3	493	3.4%
p	493	3.4%
Other values (6)	2529	17.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	46986	100.0%

Value	Count	Frequency (%)
(unknown)	14307	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	7114	15.1%
_	7046	15.0%
0	4469	9.5%
2	4203	8.9%
9	4135	8.8%
5	2806	6.0%
t	2738	5.8%
o	2738	5.8%
3	1502	3.2%
p	1502	3.2%
Other values (6)	8733	18.6%

Value	Count	Frequency (%)
.	2149	15.0%
_	2127	14.9%
0	1486	10.4%
2	1306	9.1%
9	1284	9.0%
5	828	5.8%
t	806	5.6%
o	806	5.6%
3	493	3.4%
p	493	3.4%
Other values (6)	2529	17.7%

Pulse
Real number (ℝ)

	Dataset A	Dataset B
Distinct	41	39
Distinct (%)	1.0%	3.0%
Missing	147	48
Missing (%)	3.4%	3.6%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	72.16026553	73.08597986

	Dataset A	Dataset B
Minimum	40	42
Maximum	136	122
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	40	42
5-th percentile	54	54
Q1	64	64
median	72	72
Q3	80	82
95-th percentile	92	96
Maximum	136	122
Range	96	80
Interquartile range (IQR)	16	18

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	11.5461941	12.72638278
Coefficient of variation (CV)	0.1600076443	0.1741289206
Kurtosis	0.5711985209	0.329764511
Mean	72.16026553	73.08597986
Median Absolute Deviation (MAD)	8	8
Skewness	0.4029495332	0.5474870434
Sum	304372	94354
Variance	133.3145982	161.9608188
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=41)

Value	Count	Frequency (%)
70	298	6.8%
68	285	6.5%
72	284	6.5%
74	277	6.3%
76	268	6.1%
64	265	6.1%
66	257	5.9%
78	254	5.8%
60	227	5.2%
80	203	4.7%
Other values (31)	1600	36.7%

Value	Count	Frequency (%)
68	97	7.2%
70	87	6.5%
66	85	6.3%
72	82	6.1%
64	82	6.1%
80	73	5.5%
60	70	5.2%
82	69	5.2%
76	65	4.9%
62	59	4.4%
Other values (29)	522	39.0%

Value	Count	Frequency (%)
40	9	0.2%
42	3	0.1%
44	8	0.2%
46	3	0.1%
48	15	0.3%

Value	Count	Frequency (%)
42	1	0.1%
44	3	0.2%
46	2	0.1%
48	12	0.9%
50	12	0.9%

Value	Count	Frequency (%)
42	1	< 0.1%
44	3	0.1%
46	2	< 0.1%
48	12	0.3%
50	12	0.3%

Value	Count	Frequency (%)
40	9	0.7%
42	3	0.2%
44	8	0.6%
46	3	0.2%
48	15	1.1%

BPSysAve
Real number (ℝ)

	Dataset A	Dataset B
Distinct	111	97
Distinct (%)	2.6%	7.5%
Missing	154	50
Missing (%)	3.5%	3.7%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	119.7394918	123.5120248

	Dataset A	Dataset B
Minimum	82	78
Maximum	226	221
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	82	78
5-th percentile	97	100
Q1	108	111
median	118	121
Q3	128	132
95-th percentile	148	158.6
Maximum	226	221
Range	144	143
Interquartile range (IQR)	20	21

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	16.58724306	18.23300842
Coefficient of variation (CV)	0.1385277557	0.1476213222
Kurtosis	2.64204398	2.361902326
Mean	119.7394918	123.5120248
Median Absolute Deviation (MAD)	10	10
Skewness	1.054765578	1.106364583
Sum	504223	159207
Variance	275.1366324	332.442596
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
118	152	3.5%
114	134	3.1%
119	129	3.0%
112	127	2.9%
115	118	2.7%
110	115	2.6%
116	110	2.5%
111	108	2.5%
121	107	2.5%
125	107	2.5%
Other values (101)	3004	68.8%
(Missing)	154	3.5%

Value	Count	Frequency (%)
114	59	4.4%
124	46	3.4%
115	41	3.1%
116	39	2.9%
125	38	2.8%
122	34	2.5%
112	33	2.5%
111	33	2.5%
130	32	2.4%
110	32	2.4%
Other values (87)	902	67.4%
(Missing)	50	3.7%

Value	Count	Frequency (%)
82	3	0.1%
83	1	< 0.1%
84	8	0.2%
85	7	0.2%
86	10	0.2%

Value	Count	Frequency (%)
78	1	0.1%
80	1	0.1%
81	3	0.2%
85	1	0.1%
86	1	0.1%

Value	Count	Frequency (%)
78	1	< 0.1%
80	1	< 0.1%
81	3	0.1%
85	1	< 0.1%
86	1	< 0.1%

Value	Count	Frequency (%)
82	3	0.2%
83	1	0.1%
84	8	0.6%
85	7	0.5%
86	10	0.7%

BPDiaAve
Real number (ℝ)

	Dataset A	Dataset B
Distinct	86	77
Distinct (%)	2.0%	6.0%
Missing	154	50
Missing (%)	3.5%	3.7%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	70.60128236	68.68657874

	Dataset A	Dataset B
Minimum	0	0
Maximum	116	116
Zeros	8	9
Zeros (%)	0.2%	0.7%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	52	48.4
Q1	64	61
median	71	69
Q3	78	77
95-th percentile	88	88
Maximum	116	116
Range	116	116
Interquartile range (IQR)	14	16

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	11.75212674	13.62648869
Coefficient of variation (CV)	0.1664576952	0.1983864816
Kurtosis	3.18400789	4.295346223
Mean	70.60128236	68.68657874
Median Absolute Deviation (MAD)	7	8
Skewness	-0.5792421573	-0.9348834165
Sum	297302	88537
Variance	138.1124829	185.681194
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
69	182	4.2%
72	177	4.1%
70	172	3.9%
67	164	3.8%
71	163	3.7%
68	159	3.6%
75	154	3.5%
77	151	3.5%
74	149	3.4%
66	144	3.3%
Other values (76)	2596	59.5%
(Missing)	154	3.5%

Value	Count	Frequency (%)
69	63	4.7%
68	57	4.3%
73	49	3.7%
65	48	3.6%
72	46	3.4%
70	43	3.2%
66	39	2.9%
75	39	2.9%
64	38	2.8%
74	38	2.8%
Other values (67)	829	61.9%
(Missing)	50	3.7%

Value	Count	Frequency (%)
0	8	0.2%
19	1	< 0.1%
21	3	0.1%
22	1	< 0.1%
25	1	< 0.1%

Value	Count	Frequency (%)
0	9	0.7%
15	1	0.1%
21	2	0.1%
24	2	0.1%
29	2	0.1%

Value	Count	Frequency (%)
0	9	0.2%
15	1	< 0.1%
21	2	< 0.1%
24	2	< 0.1%
29	2	< 0.1%

Value	Count	Frequency (%)
0	8	0.6%
19	1	0.1%
21	3	0.2%
22	1	0.1%
25	1	0.1%

BPSys1
Real number (ℝ)

	Dataset A	Dataset B
Distinct	60	56
Distinct (%)	1.5%	4.5%
Missing	302	96
Missing (%)	6.9%	7.2%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	120.5990647	125.1069992

	Dataset A	Dataset B
Minimum	80	74
Maximum	232	224
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	80	74
5-th percentile	98	102
Q1	110	112
median	118	122
Q3	130	134
95-th percentile	150	159.8
Maximum	232	224
Range	152	150
Interquartile range (IQR)	20	22

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	16.59386767	18.67073733
Coefficient of variation (CV)	0.1375953264	0.1492381517
Kurtosis	2.240375431	2.142772495
Mean	120.5990647	125.1069992
Median Absolute Deviation (MAD)	10	10
Skewness	0.9760239732	1.058027039
Sum	489994	155508
Variance	275.3564442	348.5964325
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
114	271	6.2%
116	244	5.6%
124	235	5.4%
118	233	5.3%
106	202	4.6%
112	195	4.5%
126	185	4.2%
122	184	4.2%
110	175	4.0%
120	168	3.8%
Other values (50)	1971	45.2%
(Missing)	302	6.9%

Value	Count	Frequency (%)
124	79	5.9%
114	74	5.5%
118	64	4.8%
112	64	4.8%
110	59	4.4%
120	58	4.3%
128	58	4.3%
116	57	4.3%
130	47	3.5%
122	46	3.4%
Other values (46)	637	47.6%
(Missing)	96	7.2%

Value	Count	Frequency (%)
80	2	< 0.1%
82	1	< 0.1%
84	10	0.2%
86	3	0.1%
88	10	0.2%

Value	Count	Frequency (%)
74	1	0.1%
78	1	0.1%
82	2	0.1%
92	10	0.7%
94	8	0.6%

Value	Count	Frequency (%)
74	1	< 0.1%
78	1	< 0.1%
82	2	< 0.1%
92	10	0.2%
94	8	0.2%

Value	Count	Frequency (%)
80	2	0.1%
82	1	0.1%
84	10	0.7%
86	3	0.2%
88	10	0.7%

BPDia1
Real number (ℝ)

	Dataset A	Dataset B
Distinct	46	39
Distinct (%)	1.1%	3.1%
Missing	302	96
Missing (%)	6.9%	7.2%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	71.18779227	69.53660499

	Dataset A	Dataset B
Minimum	0	0
Maximum	118	110
Zeros	7	7
Zeros (%)	0.2%	0.5%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	52	50
Q1	64	62
median	72	70
Q3	78	78
95-th percentile	90	88
Maximum	118	110
Range	118	110
Interquartile range (IQR)	14	16

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	11.53488612	13.01049633
Coefficient of variation (CV)	0.1620346095	0.1871028408
Kurtosis	2.788502944	4.578255596
Mean	71.18779227	69.53660499
Median Absolute Deviation (MAD)	6	8
Skewness	-0.3979440575	-0.8992679765
Sum	289236	86434
Variance	133.0535979	169.2730149
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
74	325	7.4%
72	308	7.1%
70	302	6.9%
68	296	6.8%
66	287	6.6%
76	259	5.9%
78	257	5.9%
64	255	5.8%
62	218	5.0%
80	195	4.5%
Other values (36)	1361	31.2%
(Missing)	302	6.9%

Value	Count	Frequency (%)
66	100	7.5%
68	97	7.2%
62	81	6.0%
64	80	6.0%
76	78	5.8%
72	76	5.7%
74	73	5.5%
70	73	5.5%
78	60	4.5%
82	60	4.5%
Other values (29)	465	34.7%
(Missing)	96	7.2%

Value	Count	Frequency (%)
0	7	0.2%
20	1	< 0.1%
22	1	< 0.1%
28	4	0.1%
30	1	< 0.1%

Value	Count	Frequency (%)
0	7	0.5%
10	2	0.1%
24	1	0.1%
34	3	0.2%
36	1	0.1%

Value	Count	Frequency (%)
0	7	0.2%
10	2	< 0.1%
24	1	< 0.1%
34	3	0.1%
36	1	< 0.1%

Value	Count	Frequency (%)
0	7	0.5%
20	1	0.1%
22	1	0.1%
28	4	0.3%
30	1	0.1%

BPSys2
Real number (ℝ)

	Dataset A	Dataset B
Distinct	60	57
Distinct (%)	1.5%	4.5%
Missing	244	85
Missing (%)	5.6%	6.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	120.0485319	123.8341308

	Dataset A	Dataset B
Minimum	82	78
Maximum	226	226
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	82	78
5-th percentile	96	100
Q1	108	112
median	118	122
Q3	128	134
95-th percentile	148	160
Maximum	226	226
Range	144	148
Interquartile range (IQR)	20	22

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	16.81450984	18.65205194
Coefficient of variation (CV)	0.1400642688	0.150621253
Kurtosis	2.738677052	2.595075861
Mean	120.0485319	123.8341308
Median Absolute Deviation (MAD)	10	10
Skewness	1.061128071	1.141391899
Sum	494720	155288
Variance	282.7277412	347.8990417
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
118	267	6.1%
116	246	5.6%
114	223	5.1%
124	213	4.9%
112	200	4.6%
110	198	4.5%
108	182	4.2%
106	181	4.1%
120	179	4.1%
126	178	4.1%
Other values (50)	2054	47.1%
(Missing)	244	5.6%

Value	Count	Frequency (%)
114	107	8.0%
124	76	5.7%
118	65	4.9%
116	64	4.8%
126	59	4.4%
112	57	4.3%
108	55	4.1%
132	55	4.1%
110	52	3.9%
122	49	3.7%
Other values (47)	615	45.9%
(Missing)	85	6.3%

Value	Count	Frequency (%)
82	1	< 0.1%
84	5	0.1%
86	21	0.5%
88	14	0.3%
90	20	0.5%

Value	Count	Frequency (%)
78	2	0.1%
82	3	0.2%
84	1	0.1%
86	2	0.1%
88	1	0.1%

Value	Count	Frequency (%)
78	2	< 0.1%
82	3	0.1%
84	1	< 0.1%
86	2	< 0.1%
88	1	< 0.1%

Value	Count	Frequency (%)
82	1	0.1%
84	5	0.4%
86	21	1.6%
88	14	1.0%
90	20	1.5%

BPDia2
Real number (ℝ)

	Dataset A	Dataset B
Distinct	46	43
Distinct (%)	1.1%	3.4%
Missing	244	85
Missing (%)	5.6%	6.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	70.59354526	68.97129187

	Dataset A	Dataset B
Minimum	0	0
Maximum	118	116
Zeros	13	9
Zeros (%)	0.3%	0.7%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	52	50
Q1	64	62
median	72	70
Q3	78	78
95-th percentile	88	88
Maximum	118	116
Range	118	116
Interquartile range (IQR)	14	16

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	11.89648096	13.61601349
Coefficient of variation (CV)	0.1685208034	0.1974156655
Kurtosis	3.862730782	4.55975518
Mean	70.59354526	68.97129187
Median Absolute Deviation (MAD)	6	8
Skewness	-0.6833681222	-0.942156728
Sum	290916	86490
Variance	141.5262593	185.3958232
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
72	339	7.8%
74	327	7.5%
70	321	7.4%
66	295	6.8%
68	280	6.4%
78	267	6.1%
64	263	6.0%
76	253	5.8%
62	185	4.2%
80	171	3.9%
Other values (36)	1420	32.5%
(Missing)	244	5.6%

Value	Count	Frequency (%)
70	96	7.2%
72	90	6.7%
66	86	6.4%
62	82	6.1%
74	80	6.0%
68	76	5.7%
64	71	5.3%
78	68	5.1%
76	63	4.7%
82	60	4.5%
Other values (33)	482	36.0%
(Missing)	85	6.3%

Value	Count	Frequency (%)
0	13	0.3%
24	1	< 0.1%
26	1	< 0.1%
28	1	< 0.1%
30	6	0.1%

Value	Count	Frequency (%)
0	9	0.7%
10	2	0.1%
22	1	0.1%
30	1	0.1%
34	1	0.1%

Value	Count	Frequency (%)
0	9	0.2%
10	2	< 0.1%
22	1	< 0.1%
30	1	< 0.1%
34	1	< 0.1%

Value	Count	Frequency (%)
0	13	1.0%
24	1	0.1%
26	1	0.1%
28	1	0.1%
30	6	0.4%

BPSys3
Real number (ℝ)

	Dataset A	Dataset B
Distinct	60	56
Distinct (%)	1.4%	4.4%
Missing	223	79
Missing (%)	5.1%	5.9%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	119.3756639	123.2984127

	Dataset A	Dataset B
Minimum	76	80
Maximum	226	216
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	76	80
5-th percentile	96	100
Q1	108	110
median	118	120
Q3	128	132
95-th percentile	148	158
Maximum	226	216
Range	150	136
Interquartile range (IQR)	20	22

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	16.60942048	18.24734733
Coefficient of variation (CV)	0.1391357328	0.1479933677
Kurtosis	2.456430106	2.04840905
Mean	119.3756639	123.2984127
Median Absolute Deviation (MAD)	10	10
Skewness	0.9939181346	1.067692717
Sum	494454	155356
Variance	275.8728488	332.9656845
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
114	283	6.5%
116	236	5.4%
112	217	5.0%
118	213	4.9%
104	212	4.9%
124	202	4.6%
126	197	4.5%
120	197	4.5%
106	192	4.4%
122	177	4.1%
Other values (50)	2016	46.2%
(Missing)	223	5.1%

Value	Count	Frequency (%)
114	82	6.1%
106	72	5.4%
116	72	5.4%
126	68	5.1%
120	59	4.4%
118	58	4.3%
108	58	4.3%
124	55	4.1%
110	54	4.0%
122	52	3.9%
Other values (46)	630	47.1%
(Missing)	79	5.9%

Value	Count	Frequency (%)
76	1	< 0.1%
80	2	< 0.1%
82	7	0.2%
84	14	0.3%
86	12	0.3%

Value	Count	Frequency (%)
80	3	0.2%
82	1	0.1%
84	2	0.1%
88	4	0.3%
90	3	0.2%

Value	Count	Frequency (%)
80	3	0.1%
82	1	< 0.1%
84	2	< 0.1%
88	4	0.1%
90	3	0.1%

Value	Count	Frequency (%)
76	1	0.1%
80	2	0.1%
82	7	0.5%
84	14	1.0%
86	12	0.9%

BPDia3
Real number (ℝ)

	Dataset A	Dataset B
Distinct	45	40
Distinct (%)	1.1%	3.2%
Missing	223	79
Missing (%)	5.1%	5.9%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	70.48768711	68.32222222

	Dataset A	Dataset B
Minimum	0	0
Maximum	114	116
Zeros	17	14
Zeros (%)	0.4%	1.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	52	46
Q1	64	62
median	70	68
Q3	78	78
95-th percentile	88	88
Maximum	114	116
Range	114	116
Interquartile range (IQR)	14	16

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	12.15125308	14.27921883
Coefficient of variation (CV)	0.1723883075	0.2089981614
Kurtosis	4.392492712	4.770120947
Mean	70.48768711	68.32222222
Median Absolute Deviation (MAD)	8	8
Skewness	-0.7883435228	-1.087355986
Sum	291960	86086
Variance	147.6529515	203.8960904
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=45)

Value	Count	Frequency (%)
68	324	7.4%
72	303	6.9%
78	300	6.9%
66	293	6.7%
76	291	6.7%
70	280	6.4%
74	278	6.4%
64	253	5.8%
62	214	4.9%
80	184	4.2%
Other values (35)	1422	32.6%
(Missing)	223	5.1%

Value	Count	Frequency (%)
64	93	6.9%
68	90	6.7%
72	83	6.2%
70	82	6.1%
76	72	5.4%
66	71	5.3%
62	68	5.1%
74	67	5.0%
60	65	4.9%
78	64	4.8%
Other values (30)	505	37.7%
(Missing)	79	5.9%

Value	Count	Frequency (%)
0	17	0.4%
28	1	< 0.1%
30	1	< 0.1%
32	5	0.1%
34	2	< 0.1%

Value	Count	Frequency (%)
0	14	1.0%
32	2	0.1%
34	2	0.1%
36	7	0.5%
38	6	0.4%

Value	Count	Frequency (%)
0	14	0.3%
32	2	< 0.1%
34	2	< 0.1%
36	7	0.2%
38	6	0.1%

Value	Count	Frequency (%)
0	17	1.3%
28	1	0.1%
30	1	0.1%
32	5	0.4%
34	2	0.1%

Testosterone
Real number (ℝ)

	Dataset A	Dataset B
Distinct	1171	370
Distinct (%)	54.3%	68.0%
Missing	2208	795
Missing (%)	50.6%	59.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	212.6698563	225.5515625

	Dataset A	Dataset B
Minimum	0.65	0.25
Maximum	1795.6	1244.73
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0.65	0.25
5-th percentile	9.068	7.9435
Q1	19.73	20.62
median	59.02	196.04
Q3	386.91	367.815
95-th percentile	636.6	600
Maximum	1795.6	1244.73
Range	1794.95	1244.48
Interquartile range (IQR)	367.18	347.195

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	231.7978659	220.4822143
Coefficient of variation (CV)	1.08994227	0.9775246593
Kurtosis	0.977950311	0.4742514126
Mean	212.6698563	225.5515625
Median Absolute Deviation (MAD)	51.48	175.42
Skewness	1.042675194	0.8821588005
Sum	458728.88	122700.05
Variance	53730.25063	48612.40681
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
25.54	8	0.2%
23.02	8	0.2%
579.1	7	0.2%
246.82	7	0.2%
367.35	7	0.2%
18.25	7	0.2%
350	6	0.1%
15.96	6	0.1%
23.24	6	0.1%
15.22	6	0.1%
Other values (1161)	2089	47.9%
(Missing)	2208	50.6%

Value	Count	Frequency (%)
174.1	6	0.4%
12.26	5	0.4%
4.55	5	0.4%
15.16	4	0.3%
17.3	4	0.3%
20.62	4	0.3%
683.12	4	0.3%
8.67	4	0.3%
311.09	4	0.3%
39.6	4	0.3%
Other values (360)	500	37.3%
(Missing)	795	59.4%

Value	Count	Frequency (%)
0.65	2	< 0.1%
1.79	1	< 0.1%
2.35	1	< 0.1%
2.72	1	< 0.1%
3.39	1	< 0.1%

Value	Count	Frequency (%)
0.25	1	0.1%
1.52	1	0.1%
1.98	1	0.1%
3.22	2	0.1%
3.32	1	0.1%

Value	Count	Frequency (%)
0.25	1	< 0.1%
1.52	1	< 0.1%
1.98	1	< 0.1%
3.22	2	< 0.1%
3.32	1	< 0.1%

Value	Count	Frequency (%)
0.65	2	0.1%
1.79	1	0.1%
2.35	1	0.1%
2.72	1	0.1%
3.39	1	0.1%

DirectChol
Real number (ℝ)

	Dataset A	Dataset B
Distinct	98	80
Distinct (%)	2.4%	6.5%
Missing	209	99
Missing (%)	4.8%	7.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	1.414480269	1.274145161

	Dataset A	Dataset B
Minimum	0.52	0.39
Maximum	3.83	4.03
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0.52	0.39
5-th percentile	0.85	0.78
Q1	1.11	1.01
median	1.34	1.22
Q3	1.66	1.47
95-th percentile	2.22	1.97
Maximum	3.83	4.03
Range	3.31	3.64
Interquartile range (IQR)	0.55	0.46

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	0.4309245029	0.3811940099
Coefficient of variation (CV)	0.3046521837	0.2991762803
Kurtosis	1.666444028	3.855635674
Mean	1.414480269	1.274145161
Median Absolute Deviation (MAD)	0.28	0.24
Skewness	0.988975258	1.206519196
Sum	5878.58	1579.94
Variance	0.1856959272	0.1453088732
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.24	146	3.3%
1.19	124	2.8%
1.29	119	2.7%
1.11	117	2.7%
1.32	111	2.5%
1.06	109	2.5%
1.14	109	2.5%
1.37	108	2.5%
1.4	105	2.4%
1.5	104	2.4%
Other values (88)	3004	68.8%
(Missing)	209	4.8%

Value	Count	Frequency (%)
0.98	53	4.0%
1.32	50	3.7%
1.11	44	3.3%
1.19	42	3.1%
0.96	40	3.0%
1.16	40	3.0%
1.06	40	3.0%
1.22	37	2.8%
1.29	36	2.7%
1.24	35	2.6%
Other values (70)	823	61.5%
(Missing)	99	7.4%

Value	Count	Frequency (%)
0.52	2	< 0.1%
0.54	3	0.1%
0.57	3	0.1%
0.59	4	0.1%
0.62	2	< 0.1%

Value	Count	Frequency (%)
0.39	3	0.2%
0.41	1	0.1%
0.47	1	0.1%
0.54	1	0.1%
0.57	4	0.3%

Value	Count	Frequency (%)
0.39	3	0.1%
0.41	1	< 0.1%
0.47	1	< 0.1%
0.54	1	< 0.1%
0.57	4	0.1%

Value	Count	Frequency (%)
0.52	2	0.1%
0.54	3	0.2%
0.57	3	0.2%
0.59	4	0.3%
0.62	2	0.1%

TotChol
Real number (ℝ)

	Dataset A	Dataset B
Distinct	219	187
Distinct (%)	5.3%	15.1%
Missing	209	99
Missing (%)	4.8%	7.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	5.080510106	5.004508065

	Dataset A	Dataset B
Minimum	1.53	2.17
Maximum	13.65	10.29
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1.53	2.17
5-th percentile	3.54	3.34
Q1	4.32	4.29
median	5.02	4.94
Q3	5.69	5.645
95-th percentile	6.83	6.78
Maximum	13.65	10.29
Range	12.12	8.12
Interquartile range (IQR)	1.37	1.355

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.040029635	1.057549858
Coefficient of variation (CV)	0.2047096872	0.2113194433
Kurtosis	1.982036038	0.740846084
Mean	5.080510106	5.004508065
Median Absolute Deviation (MAD)	0.7	0.685
Skewness	0.74748916	0.415698943
Sum	21114.6	6205.59
Variance	1.081661641	1.118411703
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.84	63	1.4%
4.78	62	1.4%
4.81	55	1.3%
5.02	54	1.2%
5.2	53	1.2%
5.15	51	1.2%
5.04	50	1.1%
4.24	49	1.1%
4.86	49	1.1%
5.43	48	1.1%
Other values (209)	3622	83.0%
(Missing)	209	4.8%

Value	Count	Frequency (%)
4.29	25	1.9%
5.51	21	1.6%
3.88	19	1.4%
4.09	19	1.4%
4.78	18	1.3%
4.91	17	1.3%
4.19	17	1.3%
4.97	16	1.2%
4.5	16	1.2%
5.09	16	1.2%
Other values (177)	1056	78.9%
(Missing)	99	7.4%

Value	Count	Frequency (%)
1.53	2	< 0.1%
2.38	2	< 0.1%
2.74	1	< 0.1%
2.77	1	< 0.1%
2.79	3	0.1%

Value	Count	Frequency (%)
2.17	1	0.1%
2.35	1	0.1%
2.4	1	0.1%
2.43	1	0.1%
2.59	1	0.1%

Value	Count	Frequency (%)
2.17	1	< 0.1%
2.35	1	< 0.1%
2.4	1	< 0.1%
2.43	1	< 0.1%
2.59	1	< 0.1%

Value	Count	Frequency (%)
1.53	2	0.1%
2.38	2	0.1%
2.74	1	0.1%
2.77	1	0.1%
2.79	3	0.2%

UrineVol1
Real number (ℝ)

	Dataset A	Dataset B
Distinct	388	293
Distinct (%)	9.0%	22.4%
Missing	36	32
Missing (%)	0.8%	2.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	122.4377454	116.5462892

	Dataset A	Dataset B
Minimum	0	0
Maximum	488	410
Zeros	5	1
Zeros (%)	0.1%	0.1%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	18	23
Q1	51	55
median	97	93
Q3	171	157
95-th percentile	310.8	299
Maximum	488	410
Range	488	410
Interquartile range (IQR)	120	102

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	92.23179064	83.12131556
Coefficient of variation (CV)	0.7532954018	0.7132043081
Kurtosis	0.5354138132	0.8691830965
Mean	122.4377454	116.5462892
Median Absolute Deviation (MAD)	54	47
Skewness	1.071453976	1.150515489
Sum	530033	152326
Variance	8506.703205	6909.153101
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
38	58	1.3%
18	44	1.0%
60	43	1.0%
56	41	0.9%
68	40	0.9%
36	39	0.9%
106	36	0.8%
28	36	0.8%
40	35	0.8%
84	34	0.8%
Other values (378)	3923	89.9%
(Missing)	36	0.8%

Value	Count	Frequency (%)
62	17	1.3%
64	16	1.2%
36	16	1.2%
87	16	1.2%
50	14	1.0%
70	14	1.0%
38	13	1.0%
31	13	1.0%
69	13	1.0%
52	13	1.0%
Other values (283)	1162	86.8%
(Missing)	32	2.4%

Value	Count	Frequency (%)
0	5	0.1%
1	6	0.1%
3	3	0.1%
4	3	0.1%
5	5	0.1%

Value	Count	Frequency (%)
0	1	0.1%
1	3	0.2%
2	1	0.1%
4	3	0.2%
5	2	0.1%

Value	Count	Frequency (%)
0	1	< 0.1%
1	3	0.1%
2	1	< 0.1%
4	3	0.1%
5	2	< 0.1%

Value	Count	Frequency (%)
0	5	0.4%
1	6	0.4%
3	3	0.2%
4	3	0.2%
5	5	0.4%

UrineFlow1
Real number (ℝ)

	Dataset A	Dataset B
Distinct	1456	716
Distinct (%)	35.3%	58.1%
Missing	241	107
Missing (%)	5.5%	8.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	1.074409796	0.9526160714

	Dataset A	Dataset B
Minimum	0	0
Maximum	8.73	12.346
Zeros	2	1
Zeros (%)	< 0.1%	0.1%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0.19	0.16955
Q1	0.461	0.397
median	0.8	0.6775
Q3	1.35525	1.15825
95-th percentile	2.9426	2.65625
Maximum	8.73	12.346
Range	8.73	12.346
Interquartile range (IQR)	0.89425	0.76125

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	0.9601449886	0.9654069107
Coefficient of variation (CV)	0.8936487659	1.013427066
Kurtosis	9.643442489	32.90750452
Mean	1.074409796	0.9526160714
Median Absolute Deviation (MAD)	0.405	0.3355
Skewness	2.53989013	4.280652041
Sum	4430.866	1173.623
Variance	0.9218783991	0.9320105032
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	19	0.4%
0.37	16	0.4%
0.667	15	0.3%
0.646	14	0.3%
0.5	14	0.3%
0.811	14	0.3%
0.273	13	0.3%
1.214	13	0.3%
0.817	13	0.3%
0.686	12	0.3%
Other values (1446)	3981	91.2%
(Missing)	241	5.5%

Value	Count	Frequency (%)
0.373	11	0.8%
0.5	9	0.7%
0.537	7	0.5%
0.803	6	0.4%
0.252	6	0.4%
0.297	6	0.4%
0.414	6	0.4%
0.287	6	0.4%
0.633	6	0.4%
0.89	6	0.4%
Other values (706)	1163	86.9%
(Missing)	107	8.0%

Value	Count	Frequency (%)
0	2	< 0.1%
0.005	1	< 0.1%
0.006	1	< 0.1%
0.011	3	0.1%
0.014	1	< 0.1%

Value	Count	Frequency (%)
0	1	0.1%
0.006	1	0.1%
0.011	1	0.1%
0.015	2	0.1%
0.032	2	0.1%

Value	Count	Frequency (%)
0	1	< 0.1%
0.006	1	< 0.1%
0.011	1	< 0.1%
0.015	2	< 0.1%
0.032	2	< 0.1%

Value	Count	Frequency (%)
0	2	0.1%
0.005	1	0.1%
0.006	1	0.1%
0.011	3	0.2%
0.014	1	0.1%

UrineVol2
Real number (ℝ)

	Dataset A	Dataset B
Distinct	227	83
Distinct (%)	31.1%	56.5%
Missing	3634	1192
Missing (%)	83.3%	89.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	129.0930233	119.9319728

	Dataset A	Dataset B
Minimum	0	0
Maximum	408	409
Zeros	7	2
Zeros (%)	0.2%	0.1%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	24	19.5
Q1	56	52
median	110	89
Q3	187	151
95-th percentile	310	352
Maximum	408	409
Range	408	409
Interquartile range (IQR)	131	99

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	90.98429546	100.2829326
Coefficient of variation (CV)	0.7047963799	0.8361651216
Kurtosis	0.27110802	1.265476379
Mean	129.0930233	119.9319728
Median Absolute Deviation (MAD)	58	47
Skewness	0.9437307798	1.391308859
Sum	94367	17630
Variance	8278.14202	10056.66657
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
33	10	0.2%
82	10	0.2%
54	10	0.2%
110	9	0.2%
102	8	0.2%
64	8	0.2%
50	8	0.2%
118	7	0.2%
28	7	0.2%
53	7	0.2%
Other values (217)	647	14.8%
(Missing)	3634	83.3%

Value	Count	Frequency (%)
68	8	0.6%
79	4	0.3%
103	3	0.2%
52	3	0.2%
409	3	0.2%
74	3	0.2%
30	3	0.2%
112	3	0.2%
108	3	0.2%
252	3	0.2%
Other values (73)	111	8.3%
(Missing)	1192	89.0%

Value	Count	Frequency (%)
0	7	0.2%
1	3	0.1%
3	1	< 0.1%
4	1	< 0.1%
6	1	< 0.1%

Value	Count	Frequency (%)
0	2	0.1%
8	2	0.1%
10	1	0.1%
12	1	0.1%
14	1	0.1%

Value	Count	Frequency (%)
0	2	< 0.1%
8	2	< 0.1%
10	1	< 0.1%
12	1	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
0	7	0.5%
1	3	0.2%
3	1	0.1%
4	1	0.1%
6	1	0.1%

UrineFlow2
Real number (ℝ)

	Dataset A	Dataset B
Distinct	387	110
Distinct (%)	53.1%	74.8%
Missing	3636	1192
Missing (%)	83.3%	89.0%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	1.171175583	1.023816327

	Dataset A	Dataset B
Minimum	0	0
Maximum	5.474	4
Zeros	7	2
Zeros (%)	0.2%	0.1%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0.259	0.1799
Q1	0.524	0.439
median	0.803	0.691
Q3	1.485	1.365
95-th percentile	3.066	3.1966
Maximum	5.474	4
Range	5.474	4
Interquartile range (IQR)	0.961	0.926

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	0.9956887667	0.8757534136
Coefficient of variation (CV)	0.8501618213	0.8553813715
Kurtosis	3.442929776	1.379013568
Mean	1.171175583	1.023816327
Median Absolute Deviation (MAD)	0.38	0.333
Skewness	1.790281445	1.427808858
Sum	853.787	150.501
Variance	0.9913961202	0.7669440414
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.45	8	0.2%
0.55	8	0.2%
0	7	0.2%
0.482	6	0.1%
0.57	6	0.1%
0.298	6	0.1%
2.654	5	0.1%
0.42	5	0.1%
0.979	5	0.1%
0.882	5	0.1%
Other values (377)	668	15.3%
(Missing)	3636	83.3%

Value	Count	Frequency (%)
0.532	4	0.3%
1	3	0.2%
0.265	3	0.2%
3.22	3	0.2%
0.586	3	0.2%
0.898	2	0.1%
1.617	2	0.1%
2.135	2	0.1%
0.485	2	0.1%
0.447	2	0.1%
Other values (100)	121	9.0%
(Missing)	1192	89.0%

Value	Count	Frequency (%)
0	7	0.2%
0.018	1	< 0.1%
0.02	1	< 0.1%
0.022	2	< 0.1%
0.07	1	< 0.1%

Value	Count	Frequency (%)
0	2	0.1%
0.057	2	0.1%
0.115	1	0.1%
0.139	1	0.1%
0.147	1	0.1%

Value	Count	Frequency (%)
0	2	< 0.1%
0.057	2	< 0.1%
0.115	1	< 0.1%
0.139	1	< 0.1%
0.147	1	< 0.1%

Value	Count	Frequency (%)
0	7	0.5%
0.018	1	0.1%
0.02	1	0.1%
0.022	2	0.1%
0.07	1	0.1%

Diabetes
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	2
Missing (%)	0.0%	0.1%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	2
Mean length	2.085223368	2.153328347
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	9.102	2.879
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	No
2nd row	Yes	No
3rd row	No	No
4th row	No	No
5th row	No	Yes

Value	Count	Frequency (%)
no	3993	91.5%
yes	372	8.5%

Value	Count	Frequency (%)
no	1132	84.7%
yes	205	15.3%

Most occurring characters

Value	Count	Frequency (%)
N	3993	43.9%
o	3993	43.9%
Y	372	4.1%
e	372	4.1%
s	372	4.1%

Value	Count	Frequency (%)
N	1132	39.3%
o	1132	39.3%
Y	205	7.1%
e	205	7.1%
s	205	7.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9102	100.0%

Value	Count	Frequency (%)
(unknown)	2879	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	3993	43.9%
o	3993	43.9%
Y	372	4.1%
e	372	4.1%
s	372	4.1%

Value	Count	Frequency (%)
N	1132	39.3%
o	1132	39.3%
Y	205	7.1%
e	205	7.1%
s	205	7.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9102	100.0%

Value	Count	Frequency (%)
(unknown)	2879	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	3993	43.9%
o	3993	43.9%
Y	372	4.1%
e	372	4.1%
s	372	4.1%

Value	Count	Frequency (%)
N	1132	39.3%
o	1132	39.3%
Y	205	7.1%
e	205	7.1%
s	205	7.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9102	100.0%

Value	Count	Frequency (%)
(unknown)	2879	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	3993	43.9%
o	3993	43.9%
Y	372	4.1%
e	372	4.1%
s	372	4.1%

Value	Count	Frequency (%)
N	1132	39.3%
o	1132	39.3%
Y	205	7.1%
e	205	7.1%
s	205	7.1%

DiabetesAge
Real number (ℝ)

	Dataset A	Dataset B
Distinct	59	50
Distinct (%)	20.2%	28.4%
Missing	4073	1163
Missing (%)	93.3%	86.9%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	49.70890411	49.88636364

	Dataset A	Dataset B
Minimum	7	6
Maximum	77	80
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	7	6
5-th percentile	20.55	30
Q1	44	40
median	50	50
Q3	59	60
95-th percentile	72	75
Maximum	77	80
Range	70	74
Interquartile range (IQR)	15	20

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	14.15673881	14.051279
Coefficient of variation (CV)	0.2847928166	0.2816657294
Kurtosis	0.6018898092	0.4598683502
Mean	49.70890411	49.88636364
Median Absolute Deviation (MAD)	8	10
Skewness	-0.6644629053	-0.1727966237
Sum	14515	8780
Variance	200.4132538	197.4384416
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	23	0.5%
49	19	0.4%
55	19	0.4%
60	17	0.4%
48	11	0.3%
45	10	0.2%
51	9	0.2%
40	9	0.2%
46	9	0.2%
35	8	0.2%
Other values (49)	158	3.6%
(Missing)	4073	93.3%

Value	Count	Frequency (%)
55	12	0.9%
48	11	0.8%
40	11	0.8%
50	9	0.7%
45	9	0.7%
35	7	0.5%
62	7	0.5%
60	7	0.5%
58	6	0.4%
52	6	0.4%
Other values (40)	91	6.8%
(Missing)	1163	86.9%

Value	Count	Frequency (%)
7	1	< 0.1%
8	1	< 0.1%
11	2	< 0.1%
12	1	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
6	1	0.1%
7	1	0.1%
16	1	0.1%
18	2	0.1%
22	1	0.1%

Value	Count	Frequency (%)
6	1	< 0.1%
7	1	< 0.1%
16	1	< 0.1%
18	2	< 0.1%
22	1	< 0.1%

Value	Count	Frequency (%)
7	1	0.1%
8	1	0.1%
11	2	0.1%
12	1	0.1%
14	1	0.1%

HealthGen
['Text', 'Text']

	Dataset A	Dataset B
Distinct	5	5
Distinct (%)	0.1%	0.4%
Missing	420	190
Missing (%)	9.6%	14.2%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	9	9
Median length	5	4
Mean length	5.087198986	4.476936466
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	20.069	5.144
Distinct characters	17	17
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Vgood	Poor
2nd row	Good	Good
3rd row	Good	Good
4th row	Vgood	Fair
5th row	Fair	Good

Value	Count	Frequency (%)
vgood	1509	38.3%
good	1473	37.3%
excellent	556	14.1%
fair	334	8.5%
poor	73	1.9%

Value	Count	Frequency (%)
good	466	40.6%
fair	340	29.6%
vgood	203	17.7%
poor	71	6.2%
excellent	69	6.0%

Most occurring characters

Value	Count	Frequency (%)
o	6110	30.4%
d	2982	14.9%
V	1509	7.5%
g	1509	7.5%
G	1473	7.3%
l	1112	5.5%
e	1112	5.5%
c	556	2.8%
x	556	2.8%
E	556	2.8%
Other values (7)	2594	12.9%

Value	Count	Frequency (%)
o	1480	28.8%
d	669	13.0%
G	466	9.1%
r	411	8.0%
F	340	6.6%
a	340	6.6%
i	340	6.6%
g	203	3.9%
V	203	3.9%
e	138	2.7%
Other values (7)	554	10.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	20069	100.0%

Value	Count	Frequency (%)
(unknown)	5144	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	6110	30.4%
d	2982	14.9%
V	1509	7.5%
g	1509	7.5%
G	1473	7.3%
l	1112	5.5%
e	1112	5.5%
c	556	2.8%
x	556	2.8%
E	556	2.8%
Other values (7)	2594	12.9%

Value	Count	Frequency (%)
o	1480	28.8%
d	669	13.0%
G	466	9.1%
r	411	8.0%
F	340	6.6%
a	340	6.6%
i	340	6.6%
g	203	3.9%
V	203	3.9%
e	138	2.7%
Other values (7)	554	10.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	20069	100.0%

Value	Count	Frequency (%)
(unknown)	5144	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	6110	30.4%
d	2982	14.9%
V	1509	7.5%
g	1509	7.5%
G	1473	7.3%
l	1112	5.5%
e	1112	5.5%
c	556	2.8%
x	556	2.8%
E	556	2.8%
Other values (7)	2594	12.9%

Value	Count	Frequency (%)
o	1480	28.8%
d	669	13.0%
G	466	9.1%
r	411	8.0%
F	340	6.6%
a	340	6.6%
i	340	6.6%
g	203	3.9%
V	203	3.9%
e	138	2.7%
Other values (7)	554	10.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	20069	100.0%

Value	Count	Frequency (%)
(unknown)	5144	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	6110	30.4%
d	2982	14.9%
V	1509	7.5%
g	1509	7.5%
G	1473	7.3%
l	1112	5.5%
e	1112	5.5%
c	556	2.8%
x	556	2.8%
E	556	2.8%
Other values (7)	2594	12.9%

Value	Count	Frequency (%)
o	1480	28.8%
d	669	13.0%
G	466	9.1%
r	411	8.0%
F	340	6.6%
a	340	6.6%
i	340	6.6%
g	203	3.9%
V	203	3.9%
e	138	2.7%
Other values (7)	554	10.8%

DaysPhysHlthBad
Real number (ℝ)

	Dataset A	Dataset B
Distinct	27	28
Distinct (%)	0.7%	2.4%
Missing	421	194
Missing (%)	9.6%	14.5%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	3.09178499	5.180786026

	Dataset A	Dataset B
Minimum	0	0
Maximum	30	30
Zeros	2614	704
Zeros (%)	59.9%	52.6%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0	0
Q1	0	0
median	0	0
Q3	2	5
95-th percentile	21	30
Maximum	30	30
Range	30	30
Interquartile range (IQR)	2	5

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	7.101895491	9.495470824
Coefficient of variation (CV)	2.297021143	1.832824358
Kurtosis	7.463823815	1.911725581
Mean	3.09178499	5.180786026
Median Absolute Deviation (MAD)	0	0
Skewness	2.868045904	1.834858609
Sum	12194	5932
Variance	50.43691956	90.16396616
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
0	2614	59.9%
2	237	5.4%
30	177	4.1%
3	164	3.8%
1	136	3.1%
5	117	2.7%
4	111	2.5%
7	99	2.3%
10	58	1.3%
14	51	1.2%
Other values (17)	180	4.1%
(Missing)	421	9.6%

Value	Count	Frequency (%)
0	704	52.6%
30	109	8.1%
2	50	3.7%
5	40	3.0%
3	33	2.5%
1	26	1.9%
7	25	1.9%
15	25	1.9%
4	24	1.8%
10	23	1.7%
Other values (18)	86	6.4%
(Missing)	194	14.5%

Value	Count	Frequency (%)
0	2614	59.9%
1	136	3.1%
2	237	5.4%
3	164	3.8%
4	111	2.5%

Value	Count	Frequency (%)
0	704	52.6%
1	26	1.9%
2	50	3.7%
3	33	2.5%
4	24	1.8%

Value	Count	Frequency (%)
0	704	16.1%
1	26	0.6%
2	50	1.1%
3	33	0.8%
4	24	0.5%

Value	Count	Frequency (%)
0	2614	195.2%
1	136	10.2%
2	237	17.7%
3	164	12.2%
4	111	8.3%

DaysMentHlthBad
Real number (ℝ)

	Dataset A	Dataset B
Distinct	27	25
Distinct (%)	0.7%	2.2%
Missing	421	192
Missing (%)	9.6%	14.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	3.914300203	5.306887533

	Dataset A	Dataset B
Minimum	0	0
Maximum	30	30
Zeros	2269	663
Zeros (%)	52.0%	49.5%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0	0
Q1	0	0
median	0	0
Q3	4	5
95-th percentile	30	30
Maximum	30	30
Range	30	30
Interquartile range (IQR)	4	5

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	7.699284635	9.44655101
Coefficient of variation (CV)	1.966963247	1.780054873
Kurtosis	4.92835645	1.91590455
Mean	3.914300203	5.306887533
Median Absolute Deviation (MAD)	0	0
Skewness	2.415973379	1.823220326
Sum	15438	6087
Variance	59.27898389	89.23732599
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
0	2269	52.0%
2	276	6.3%
30	205	4.7%
3	200	4.6%
5	176	4.0%
1	172	3.9%
4	146	3.3%
10	98	2.2%
7	82	1.9%
15	80	1.8%
Other values (17)	240	5.5%
(Missing)	421	9.6%

Value	Count	Frequency (%)
0	663	49.5%
30	108	8.1%
2	56	4.2%
5	49	3.7%
3	41	3.1%
1	40	3.0%
15	32	2.4%
4	26	1.9%
10	25	1.9%
14	24	1.8%
Other values (15)	83	6.2%
(Missing)	192	14.3%

Value	Count	Frequency (%)
0	2269	52.0%
1	172	3.9%
2	276	6.3%
3	200	4.6%
4	146	3.3%

Value	Count	Frequency (%)
0	663	49.5%
1	40	3.0%
2	56	4.2%
3	41	3.1%
4	26	1.9%

Value	Count	Frequency (%)
0	663	15.2%
1	40	0.9%
2	56	1.3%
3	41	0.9%
4	26	0.6%

Value	Count	Frequency (%)
0	2269	169.5%
1	172	12.8%
2	276	20.6%
3	200	14.9%
4	146	10.9%

LittleInterest
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.2%	0.6%
Missing	3541	1010
Missing (%)	81.1%	75.4%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	7	7
Median length	7	7
Mean length	6.27184466	5.76899696
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	5.168	1.898
Distinct characters	10	10
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Most	Several
2nd row	Several	Several
3rd row	Several	Several
4th row	Several	Most
5th row	Most	Several

Value	Count	Frequency (%)
several	624	75.7%
most	200	24.3%

Value	Count	Frequency (%)
several	194	59.0%
most	135	41.0%

Most occurring characters

Value	Count	Frequency (%)
e	1248	24.1%
S	624	12.1%
v	624	12.1%
r	624	12.1%
a	624	12.1%
l	624	12.1%
M	200	3.9%
o	200	3.9%
s	200	3.9%
t	200	3.9%

Value	Count	Frequency (%)
e	388	20.4%
S	194	10.2%
v	194	10.2%
r	194	10.2%
a	194	10.2%
l	194	10.2%
M	135	7.1%
o	135	7.1%
s	135	7.1%
t	135	7.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5168	100.0%

Value	Count	Frequency (%)
(unknown)	1898	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1248	24.1%
S	624	12.1%
v	624	12.1%
r	624	12.1%
a	624	12.1%
l	624	12.1%
M	200	3.9%
o	200	3.9%
s	200	3.9%
t	200	3.9%

Value	Count	Frequency (%)
e	388	20.4%
S	194	10.2%
v	194	10.2%
r	194	10.2%
a	194	10.2%
l	194	10.2%
M	135	7.1%
o	135	7.1%
s	135	7.1%
t	135	7.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5168	100.0%

Value	Count	Frequency (%)
(unknown)	1898	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1248	24.1%
S	624	12.1%
v	624	12.1%
r	624	12.1%
a	624	12.1%
l	624	12.1%
M	200	3.9%
o	200	3.9%
s	200	3.9%
t	200	3.9%

Value	Count	Frequency (%)
e	388	20.4%
S	194	10.2%
v	194	10.2%
r	194	10.2%
a	194	10.2%
l	194	10.2%
M	135	7.1%
o	135	7.1%
s	135	7.1%
t	135	7.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5168	100.0%

Value	Count	Frequency (%)
(unknown)	1898	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1248	24.1%
S	624	12.1%
v	624	12.1%
r	624	12.1%
a	624	12.1%
l	624	12.1%
M	200	3.9%
o	200	3.9%
s	200	3.9%
t	200	3.9%

Value	Count	Frequency (%)
e	388	20.4%
S	194	10.2%
v	194	10.2%
r	194	10.2%
a	194	10.2%
l	194	10.2%
M	135	7.1%
o	135	7.1%
s	135	7.1%
t	135	7.1%

Depressed
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.3%	0.6%
Missing	3637	1013
Missing (%)	83.3%	75.7%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	7	7
Median length	7	7
Mean length	6.282967033	5.619631902
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	4.574	1.832
Distinct characters	10	10
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Most	Several
2nd row	Several	Most
3rd row	Most	Most
4th row	Several	Several
5th row	Several	Most

Value	Count	Frequency (%)
several	554	76.1%
most	174	23.9%

Value	Count	Frequency (%)
several	176	54.0%
most	150	46.0%

Most occurring characters

Value	Count	Frequency (%)
e	1108	24.2%
S	554	12.1%
v	554	12.1%
r	554	12.1%
a	554	12.1%
l	554	12.1%
M	174	3.8%
o	174	3.8%
s	174	3.8%
t	174	3.8%

Value	Count	Frequency (%)
e	352	19.2%
S	176	9.6%
v	176	9.6%
r	176	9.6%
a	176	9.6%
l	176	9.6%
M	150	8.2%
o	150	8.2%
s	150	8.2%
t	150	8.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4574	100.0%

Value	Count	Frequency (%)
(unknown)	1832	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1108	24.2%
S	554	12.1%
v	554	12.1%
r	554	12.1%
a	554	12.1%
l	554	12.1%
M	174	3.8%
o	174	3.8%
s	174	3.8%
t	174	3.8%

Value	Count	Frequency (%)
e	352	19.2%
S	176	9.6%
v	176	9.6%
r	176	9.6%
a	176	9.6%
l	176	9.6%
M	150	8.2%
o	150	8.2%
s	150	8.2%
t	150	8.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4574	100.0%

Value	Count	Frequency (%)
(unknown)	1832	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1108	24.2%
S	554	12.1%
v	554	12.1%
r	554	12.1%
a	554	12.1%
l	554	12.1%
M	174	3.8%
o	174	3.8%
s	174	3.8%
t	174	3.8%

Value	Count	Frequency (%)
e	352	19.2%
S	176	9.6%
v	176	9.6%
r	176	9.6%
a	176	9.6%
l	176	9.6%
M	150	8.2%
o	150	8.2%
s	150	8.2%
t	150	8.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4574	100.0%

Value	Count	Frequency (%)
(unknown)	1832	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1108	24.2%
S	554	12.1%
v	554	12.1%
r	554	12.1%
a	554	12.1%
l	554	12.1%
M	174	3.8%
o	174	3.8%
s	174	3.8%
t	174	3.8%

Value	Count	Frequency (%)
e	352	19.2%
S	176	9.6%
v	176	9.6%
r	176	9.6%
a	176	9.6%
l	176	9.6%
M	150	8.2%
o	150	8.2%
s	150	8.2%
t	150	8.2%

nPregnancies
Real number (ℝ)

	Dataset A	Dataset B
Distinct	13	12
Distinct (%)	0.8%	2.7%
Missing	2812	887
Missing (%)	64.4%	66.2%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	2.850611719	3.60619469

	Dataset A	Dataset B
Minimum	1	1
Maximum	32	12
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1	1
5-th percentile	1	1
Q1	2	2
median	3	3
Q3	4	5
95-th percentile	6	7
Maximum	32	12
Range	31	11
Interquartile range (IQR)	2	3

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.738241409	1.995506401
Coefficient of variation (CV)	0.6097783844	0.5533551493
Kurtosis	52.46199122	2.174666885
Mean	2.850611719	3.60619469
Median Absolute Deviation (MAD)	1	1
Skewness	4.029718776	1.290770789
Sum	4427	1630
Variance	3.021483195	3.982045798
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
2	466	10.7%
3	365	8.4%
1	298	6.8%
4	210	4.8%
5	127	2.9%
6	48	1.1%
7	21	0.5%
8	8	0.2%
11	4	0.1%
10	3	0.1%
Other values (3)	3	0.1%
(Missing)	2812	64.4%

Value	Count	Frequency (%)
3	113	8.4%
2	103	7.7%
4	78	5.8%
5	44	3.3%
1	43	3.2%
6	38	2.8%
7	13	1.0%
9	8	0.6%
10	6	0.4%
8	3	0.2%
Other values (2)	3	0.2%
(Missing)	887	66.2%

Value	Count	Frequency (%)
1	298	6.8%
2	466	10.7%
3	365	8.4%
4	210	4.8%
5	127	2.9%

Value	Count	Frequency (%)
1	43	3.2%
2	103	7.7%
3	113	8.4%
4	78	5.8%
5	44	3.3%

Value	Count	Frequency (%)
1	43	1.0%
2	103	2.4%
3	113	2.6%
4	78	1.8%
5	44	1.0%

Value	Count	Frequency (%)
1	298	22.3%
2	466	34.8%
3	365	27.3%
4	210	15.7%
5	127	9.5%

nBabies
Real number (ℝ)

	Dataset A	Dataset B
Distinct	10	12
Distinct (%)	0.7%	2.8%
Missing	2945	909
Missing (%)	67.5%	67.9%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	2.231690141	3.037209302

	Dataset A	Dataset B
Minimum	0	0
Maximum	11	12
Zeros	4	3
Zeros (%)	0.1%	0.2%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	1	1
Q1	2	2
median	2	3
Q3	3	4
95-th percentile	4	6
Maximum	11	12
Range	11	12
Interquartile range (IQR)	1	2

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.09607987	1.716099993
Coefficient of variation (CV)	0.4911433938	0.5650252658
Kurtosis	4.847687453	3.242262259
Mean	2.231690141	3.037209302
Median Absolute Deviation (MAD)	1	1
Skewness	1.467574625	1.435070863
Sum	3169	1306
Variance	1.201391081	2.944999187
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2	616	14.1%
1	346	7.9%
3	309	7.1%
4	93	2.1%
5	32	0.7%
6	13	0.3%
7	5	0.1%
0	4	0.1%
11	1	< 0.1%
8	1	< 0.1%
(Missing)	2945	67.5%

Value	Count	Frequency (%)
2	131	9.8%
3	112	8.4%
1	58	4.3%
4	57	4.3%
5	30	2.2%
6	22	1.6%
7	6	0.4%
8	6	0.4%
9	3	0.2%
0	3	0.2%
Other values (2)	2	0.1%
(Missing)	909	67.9%

Value	Count	Frequency (%)
0	4	0.1%
1	346	7.9%
2	616	14.1%
3	309	7.1%
4	93	2.1%

Value	Count	Frequency (%)
0	3	0.2%
1	58	4.3%
2	131	9.8%
3	112	8.4%
4	57	4.3%

Value	Count	Frequency (%)
0	3	0.1%
1	58	1.3%
2	131	3.0%
3	112	2.6%
4	57	1.3%

Value	Count	Frequency (%)
0	4	0.3%
1	346	25.8%
2	616	46.0%
3	309	23.1%
4	93	6.9%

Age1stBaby
Real number (ℝ)

	Dataset A	Dataset B
Distinct	25	20
Distinct (%)	2.3%	5.4%
Missing	3295	972
Missing (%)	75.5%	72.6%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	24.24579439	20.0626703

	Dataset A	Dataset B
Minimum	14	14
Maximum	39	37
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	14	14
5-th percentile	17	15
Q1	21	17
median	24	19
Q3	28	22
95-th percentile	33	28
Maximum	39	37
Range	25	23
Interquartile range (IQR)	7	5

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	4.868558187	3.789386452
Coefficient of variation (CV)	0.2008001102	0.1888774722
Kurtosis	-0.432024269	2.036736448
Mean	24.24579439	20.0626703
Median Absolute Deviation (MAD)	4	2
Skewness	0.3118721804	1.196598794
Sum	25943	7363
Variance	23.70285882	14.35944968
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
23	102	2.3%
24	89	2.0%
21	87	2.0%
26	70	1.6%
20	69	1.6%
25	67	1.5%
19	61	1.4%
29	60	1.4%
22	59	1.4%
28	57	1.3%
Other values (15)	349	8.0%
(Missing)	3295	75.5%

Value	Count	Frequency (%)
17	53	4.0%
18	45	3.4%
22	43	3.2%
19	43	3.2%
20	32	2.4%
21	28	2.1%
16	27	2.0%
23	21	1.6%
15	17	1.3%
24	15	1.1%
Other values (10)	43	3.2%
(Missing)	972	72.6%

Value	Count	Frequency (%)
14	3	0.1%
15	14	0.3%
16	31	0.7%
17	28	0.6%
18	53	1.2%

Value	Count	Frequency (%)
14	6	0.4%
15	17	1.3%
16	27	2.0%
17	53	4.0%
18	45	3.4%

Value	Count	Frequency (%)
14	6	0.1%
15	17	0.4%
16	27	0.6%
17	53	1.2%
18	45	1.0%

Value	Count	Frequency (%)
14	3	0.2%
15	14	1.0%
16	31	2.3%
17	28	2.1%
18	53	4.0%

SleepHrsNight
Real number (ℝ)

	Dataset A	Dataset B
Distinct	11	11
Distinct (%)	0.3%	0.8%
Missing	11	4
Missing (%)	0.3%	0.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	6.950390446	6.81423221

	Dataset A	Dataset B
Minimum	2	2
Maximum	12	12
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	2	2
5-th percentile	5	4
Q1	6	6
median	7	7
Q3	8	8
95-th percentile	9	9
Maximum	12	12
Range	10	10
Interquartile range (IQR)	2	2

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.248871242	1.506091974
Coefficient of variation (CV)	0.1796836094	0.221021522
Kurtosis	1.041102367	0.360634978
Mean	6.950390446	6.81423221
Median Absolute Deviation (MAD)	1	1
Skewness	-0.2028340671	-0.2279047704
Sum	30262	9097
Variance	1.559679379	2.268313034
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
7	1401	32.1%
8	1221	28.0%
6	982	22.5%
5	309	7.1%
9	218	5.0%
4	129	3.0%
10	47	1.1%
3	24	0.5%
12	13	0.3%
11	6	0.1%
(Missing)	11	0.3%

Value	Count	Frequency (%)
8	378	28.2%
6	328	24.5%
7	300	22.4%
5	119	8.9%
4	74	5.5%
9	63	4.7%
10	37	2.8%
3	22	1.6%
11	7	0.5%
2	5	0.4%
(Missing)	4	0.3%

Value	Count	Frequency (%)
2	4	0.1%
3	24	0.5%
4	129	3.0%
5	309	7.1%
6	982	22.5%

Value	Count	Frequency (%)
2	5	0.4%
3	22	1.6%
4	74	5.5%
5	119	8.9%
6	328	24.5%

Value	Count	Frequency (%)
2	5	0.1%
3	22	0.5%
4	74	1.7%
5	119	2.7%
6	328	7.5%

Value	Count	Frequency (%)
2	4	0.3%
3	24	1.8%
4	129	9.6%
5	309	23.1%
6	982	73.3%

SleepTrouble
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	2
Mean length	2.264146621	2.249439881
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	9.883	3.012
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	No
2nd row	Yes	Yes
3rd row	No	No
4th row	No	No
5th row	No	No

Value	Count	Frequency (%)
no	3212	73.6%
yes	1153	26.4%

Value	Count	Frequency (%)
no	1005	75.1%
yes	334	24.9%

Most occurring characters

Value	Count	Frequency (%)
N	3212	32.5%
o	3212	32.5%
Y	1153	11.7%
e	1153	11.7%
s	1153	11.7%

Value	Count	Frequency (%)
N	1005	33.4%
o	1005	33.4%
Y	334	11.1%
e	334	11.1%
s	334	11.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9883	100.0%

Value	Count	Frequency (%)
(unknown)	3012	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	3212	32.5%
o	3212	32.5%
Y	1153	11.7%
e	1153	11.7%
s	1153	11.7%

Value	Count	Frequency (%)
N	1005	33.4%
o	1005	33.4%
Y	334	11.1%
e	334	11.1%
s	334	11.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9883	100.0%

Value	Count	Frequency (%)
(unknown)	3012	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	3212	32.5%
o	3212	32.5%
Y	1153	11.7%
e	1153	11.7%
s	1153	11.7%

Value	Count	Frequency (%)
N	1005	33.4%
o	1005	33.4%
Y	334	11.1%
e	334	11.1%
s	334	11.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9883	100.0%

Value	Count	Frequency (%)
(unknown)	3012	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	3212	32.5%
o	3212	32.5%
Y	1153	11.7%
e	1153	11.7%
s	1153	11.7%

Value	Count	Frequency (%)
N	1005	33.4%
o	1005	33.4%
Y	334	11.1%
e	334	11.1%
s	334	11.1%

PhysActive
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	3	2
Mean length	2.632989691	2.291262136
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	11.493	3.068
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Yes	No
2nd row	No	Yes
3rd row	No	No
4th row	No	No
5th row	Yes	No

Value	Count	Frequency (%)
yes	2763	63.3%
no	1602	36.7%

Value	Count	Frequency (%)
no	949	70.9%
yes	390	29.1%

Most occurring characters

Value	Count	Frequency (%)
Y	2763	24.0%
e	2763	24.0%
s	2763	24.0%
N	1602	13.9%
o	1602	13.9%

Value	Count	Frequency (%)
N	949	30.9%
o	949	30.9%
Y	390	12.7%
e	390	12.7%
s	390	12.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11493	100.0%

Value	Count	Frequency (%)
(unknown)	3068	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	2763	24.0%
e	2763	24.0%
s	2763	24.0%
N	1602	13.9%
o	1602	13.9%

Value	Count	Frequency (%)
N	949	30.9%
o	949	30.9%
Y	390	12.7%
e	390	12.7%
s	390	12.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11493	100.0%

Value	Count	Frequency (%)
(unknown)	3068	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	2763	24.0%
e	2763	24.0%
s	2763	24.0%
N	1602	13.9%
o	1602	13.9%

Value	Count	Frequency (%)
N	949	30.9%
o	949	30.9%
Y	390	12.7%
e	390	12.7%
s	390	12.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11493	100.0%

Value	Count	Frequency (%)
(unknown)	3068	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	2763	24.0%
e	2763	24.0%
s	2763	24.0%
N	1602	13.9%
o	1602	13.9%

Value	Count	Frequency (%)
N	949	30.9%
o	949	30.9%
Y	390	12.7%
e	390	12.7%
s	390	12.7%

PhysActiveDays
Real number (ℝ)

	Dataset A	Dataset B
Distinct	7	7
Distinct (%)	0.3%	1.4%
Missing	1951	821
Missing (%)	44.7%	61.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	3.693040597	3.666023166

	Dataset A	Dataset B
Minimum	1	1
Maximum	7	7
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1	1
5-th percentile	1	1
Q1	2	2
median	3	3
Q3	5	5
95-th percentile	7	7
Maximum	7	7
Range	6	6
Interquartile range (IQR)	3	3

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.811180349	1.916649038
Coefficient of variation (CV)	0.4904306632	0.5228142189
Kurtosis	-0.8321744695	-0.9614052895
Mean	3.693040597	3.666023166
Median Absolute Deviation (MAD)	1	1
Skewness	0.3468209776	0.4013099512
Sum	8915	1899
Variance	3.280374257	3.673543535
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
3	617	14.1%
5	396	9.1%
2	389	8.9%
4	316	7.2%
1	282	6.5%
7	276	6.3%
6	138	3.2%
(Missing)	1951	44.7%

Value	Count	Frequency (%)
2	112	8.4%
3	100	7.5%
5	75	5.6%
7	74	5.5%
4	70	5.2%
1	64	4.8%
6	23	1.7%
(Missing)	821	61.3%

Value	Count	Frequency (%)
1	282	6.5%
2	389	8.9%
3	617	14.1%
4	316	7.2%
5	396	9.1%

Value	Count	Frequency (%)
1	64	4.8%
2	112	8.4%
3	100	7.5%
4	70	5.2%
5	75	5.6%

Value	Count	Frequency (%)
1	64	1.5%
2	112	2.6%
3	100	2.3%
4	70	1.6%
5	75	1.7%

Value	Count	Frequency (%)
1	282	21.1%
2	389	29.1%
3	617	46.1%
4	316	23.6%
5	396	29.6%

TVHrsDay
['Text', 'Text']

	Dataset A	Dataset B
Distinct	7	7
Distinct (%)	0.3%	1.1%
Missing	2078	723
Missing (%)	47.6%	54.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	9	9
Median length	4	4
Mean length	5.314822912	5.563311688
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	12.155	3.427
Distinct characters	13	13
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	3_hr	4_hr
2nd row	More_4_hr	More_4_hr
3rd row	2_hr	2_hr
4th row	3_hr	0_to_1_hr
5th row	2_hr	More_4_hr

Value	Count	Frequency (%)
2_hr	628	27.5%
1_hr	414	18.1%
3_hr	377	16.5%
0_to_1_hr	349	15.3%
more_4_hr	243	10.6%
4_hr	229	10.0%
0_hrs	47	2.1%

Value	Count	Frequency (%)
more_4_hr	143	23.2%
3_hr	120	19.5%
2_hr	116	18.8%
1_hr	93	15.1%
4_hr	80	13.0%
0_to_1_hr	46	7.5%
0_hrs	18	2.9%

Most occurring characters

Value	Count	Frequency (%)
_	3228	26.6%
r	2530	20.8%
h	2287	18.8%
1	763	6.3%
2	628	5.2%
o	592	4.9%
4	472	3.9%
0	396	3.3%
3	377	3.1%
t	349	2.9%
Other values (3)	533	4.4%

Value	Count	Frequency (%)
_	851	24.8%
r	759	22.1%
h	616	18.0%
4	223	6.5%
o	189	5.5%
M	143	4.2%
e	143	4.2%
1	139	4.1%
3	120	3.5%
2	116	3.4%
Other values (3)	128	3.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	12155	100.0%

Value	Count	Frequency (%)
(unknown)	3427	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
_	3228	26.6%
r	2530	20.8%
h	2287	18.8%
1	763	6.3%
2	628	5.2%
o	592	4.9%
4	472	3.9%
0	396	3.3%
3	377	3.1%
t	349	2.9%
Other values (3)	533	4.4%

Value	Count	Frequency (%)
_	851	24.8%
r	759	22.1%
h	616	18.0%
4	223	6.5%
o	189	5.5%
M	143	4.2%
e	143	4.2%
1	139	4.1%
3	120	3.5%
2	116	3.4%
Other values (3)	128	3.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	12155	100.0%

Value	Count	Frequency (%)
(unknown)	3427	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
_	3228	26.6%
r	2530	20.8%
h	2287	18.8%
1	763	6.3%
2	628	5.2%
o	592	4.9%
4	472	3.9%
0	396	3.3%
3	377	3.1%
t	349	2.9%
Other values (3)	533	4.4%

Value	Count	Frequency (%)
_	851	24.8%
r	759	22.1%
h	616	18.0%
4	223	6.5%
o	189	5.5%
M	143	4.2%
e	143	4.2%
1	139	4.1%
3	120	3.5%
2	116	3.4%
Other values (3)	128	3.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	12155	100.0%

Value	Count	Frequency (%)
(unknown)	3427	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
_	3228	26.6%
r	2530	20.8%
h	2287	18.8%
1	763	6.3%
2	628	5.2%
o	592	4.9%
4	472	3.9%
0	396	3.3%
3	377	3.1%
t	349	2.9%
Other values (3)	533	4.4%

Value	Count	Frequency (%)
_	851	24.8%
r	759	22.1%
h	616	18.0%
4	223	6.5%
o	189	5.5%
M	143	4.2%
e	143	4.2%
1	139	4.1%
3	120	3.5%
2	116	3.4%
Other values (3)	128	3.7%

CompHrsDay
['Text', 'Text']

	Dataset A	Dataset B
Distinct	7	7
Distinct (%)	0.3%	1.1%
Missing	2077	722
Missing (%)	47.6%	53.9%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	9	9
Median length	4	5
Mean length	5.914335664	5.883306321
Min length	4	4

Characters and Unicode

	Dataset A	Dataset B
Total characters	13.532	3.630
Distinct characters	13	13
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	1_hr	2_hr
2nd row	More_4_hr	0_hrs
3rd row	0_to_1_hr	0_hrs
4th row	1_hr	0_hrs
5th row	0_to_1_hr	2_hr

Value	Count	Frequency (%)
0_to_1_hr	664	29.0%
1_hr	579	25.3%
2_hr	327	14.3%
0_hrs	270	11.8%
3_hr	169	7.4%
more_4_hr	158	6.9%
4_hr	121	5.3%

Value	Count	Frequency (%)
0_hrs	317	51.4%
0_to_1_hr	148	24.0%
1_hr	49	7.9%
2_hr	45	7.3%
3_hr	31	5.0%
more_4_hr	21	3.4%
4_hr	6	1.0%

Most occurring characters

Value	Count	Frequency (%)
_	3774	27.9%
r	2446	18.1%
h	2288	16.9%
1	1243	9.2%
0	934	6.9%
o	822	6.1%
t	664	4.9%
2	327	2.4%
4	279	2.1%
s	270	2.0%
Other values (3)	485	3.6%

Value	Count	Frequency (%)
_	934	25.7%
r	638	17.6%
h	617	17.0%
0	465	12.8%
s	317	8.7%
1	197	5.4%
o	169	4.7%
t	148	4.1%
2	45	1.2%
3	31	0.9%
Other values (3)	69	1.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13532	100.0%

Value	Count	Frequency (%)
(unknown)	3630	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
_	3774	27.9%
r	2446	18.1%
h	2288	16.9%
1	1243	9.2%
0	934	6.9%
o	822	6.1%
t	664	4.9%
2	327	2.4%
4	279	2.1%
s	270	2.0%
Other values (3)	485	3.6%

Value	Count	Frequency (%)
_	934	25.7%
r	638	17.6%
h	617	17.0%
0	465	12.8%
s	317	8.7%
1	197	5.4%
o	169	4.7%
t	148	4.1%
2	45	1.2%
3	31	0.9%
Other values (3)	69	1.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13532	100.0%

Value	Count	Frequency (%)
(unknown)	3630	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
_	3774	27.9%
r	2446	18.1%
h	2288	16.9%
1	1243	9.2%
0	934	6.9%
o	822	6.1%
t	664	4.9%
2	327	2.4%
4	279	2.1%
s	270	2.0%
Other values (3)	485	3.6%

Value	Count	Frequency (%)
_	934	25.7%
r	638	17.6%
h	617	17.0%
0	465	12.8%
s	317	8.7%
1	197	5.4%
o	169	4.7%
t	148	4.1%
2	45	1.2%
3	31	0.9%
Other values (3)	69	1.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13532	100.0%

Value	Count	Frequency (%)
(unknown)	3630	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
_	3774	27.9%
r	2446	18.1%
h	2288	16.9%
1	1243	9.2%
0	934	6.9%
o	822	6.1%
t	664	4.9%
2	327	2.4%
4	279	2.1%
s	270	2.0%
Other values (3)	485	3.6%

Value	Count	Frequency (%)
_	934	25.7%
r	638	17.6%
h	617	17.0%
0	465	12.8%
s	317	8.7%
1	197	5.4%
o	169	4.7%
t	148	4.1%
2	45	1.2%
3	31	0.9%
Other values (3)	69	1.9%

TVHrsDayChild
[None, None]

	Dataset A	Dataset B
Missing	4365	1339
Missing (%)	100.0%	100.0%
Memory size	197.2 KiB	53.2 KiB

CompHrsDayChild
[None, None]

	Dataset A	Dataset B
Missing	4365	1339
Missing (%)	100.0%	100.0%
Memory size	197.2 KiB	53.2 KiB

Alcohol12PlusYr
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.2%
Missing	423	199
Missing (%)	9.7%	14.9%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	3	3
Mean length	2.820649417	2.736842105
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	11.119	3.120
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Yes	Yes
2nd row	Yes	Yes
3rd row	Yes	Yes
4th row	Yes	No
5th row	No	Yes

Value	Count	Frequency (%)
yes	3235	82.1%
no	707	17.9%

Value	Count	Frequency (%)
yes	840	73.7%
no	300	26.3%

Most occurring characters

Value	Count	Frequency (%)
Y	3235	29.1%
e	3235	29.1%
s	3235	29.1%
N	707	6.4%
o	707	6.4%

Value	Count	Frequency (%)
Y	840	26.9%
e	840	26.9%
s	840	26.9%
N	300	9.6%
o	300	9.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11119	100.0%

Value	Count	Frequency (%)
(unknown)	3120	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	3235	29.1%
e	3235	29.1%
s	3235	29.1%
N	707	6.4%
o	707	6.4%

Value	Count	Frequency (%)
Y	840	26.9%
e	840	26.9%
s	840	26.9%
N	300	9.6%
o	300	9.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11119	100.0%

Value	Count	Frequency (%)
(unknown)	3120	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	3235	29.1%
e	3235	29.1%
s	3235	29.1%
N	707	6.4%
o	707	6.4%

Value	Count	Frequency (%)
Y	840	26.9%
e	840	26.9%
s	840	26.9%
N	300	9.6%
o	300	9.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11119	100.0%

Value	Count	Frequency (%)
(unknown)	3120	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	3235	29.1%
e	3235	29.1%
s	3235	29.1%
N	707	6.4%
o	707	6.4%

Value	Count	Frequency (%)
Y	840	26.9%
e	840	26.9%
s	840	26.9%
N	300	9.6%
o	300	9.6%

AlcoholDay
Real number (ℝ)

	Dataset A	Dataset B
Distinct	17	18
Distinct (%)	0.5%	2.5%
Missing	1208	626
Missing (%)	27.7%	46.8%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	2.442191954	4.100981767

	Dataset A	Dataset B
Minimum	1	1
Maximum	30	82
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1	1
5-th percentile	1	1
Q1	1	2
median	2	3
Q3	3	6
95-th percentile	6	12
Maximum	30	82
Range	29	81
Interquartile range (IQR)	2	4

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	2.060914869	4.527805684
Coefficient of variation (CV)	0.8438791495	1.104078472
Kurtosis	28.3006606	123.7077335
Mean	2.442191954	4.100981767
Median Absolute Deviation (MAD)	1	2
Skewness	3.753514054	7.999501334
Sum	7710	2924
Variance	4.247370099	20.50102432
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	1202	27.5%
2	958	21.9%
3	409	9.4%
4	231	5.3%
6	133	3.0%
5	121	2.8%
7	28	0.6%
8	23	0.5%
12	21	0.5%
10	14	0.3%
Other values (7)	17	0.4%
(Missing)	1208	27.7%

Value	Count	Frequency (%)
1	163	12.2%
2	162	12.1%
3	103	7.7%
6	77	5.8%
4	52	3.9%
5	50	3.7%
12	31	2.3%
10	24	1.8%
8	18	1.3%
7	16	1.2%
Other values (8)	17	1.3%
(Missing)	626	46.8%

Value	Count	Frequency (%)
1	1202	27.5%
2	958	21.9%
3	409	9.4%
4	231	5.3%
5	121	2.8%

Value	Count	Frequency (%)
1	163	12.2%
2	162	12.1%
3	103	7.7%
4	52	3.9%
5	50	3.7%

Value	Count	Frequency (%)
1	163	3.7%
2	162	3.7%
3	103	2.4%
4	52	1.2%
5	50	1.1%

Value	Count	Frequency (%)
1	1202	89.8%
2	958	71.5%
3	409	30.5%
4	231	17.3%
5	121	9.0%

AlcoholYear
Real number (ℝ)

	Dataset A	Dataset B
Distinct	58	37
Distinct (%)	1.6%	3.8%
Missing	733	355
Missing (%)	16.8%	26.5%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	82.7535793	59.05894309

	Dataset A	Dataset B
Minimum	0	0
Maximum	364	364
Zeros	473	270
Zeros (%)	10.8%	20.2%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0	0
Q1	5	0
median	36	12
Q3	104	52
95-th percentile	364	364
Maximum	364	364
Range	364	364
Interquartile range (IQR)	99	52

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	104.0034643	101.0941293
Coefficient of variation (CV)	1.256785086	1.711749719
Kurtosis	0.9261815492	3.247306627
Mean	82.7535793	59.05894309
Median Absolute Deviation (MAD)	35	12
Skewness	1.402414672	2.077355401
Sum	300561	58114
Variance	10816.72059	10220.02297
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	473	10.8%
52	403	9.2%
104	355	8.1%
12	321	7.4%
24	299	6.8%
156	240	5.5%
364	189	4.3%
208	178	4.1%
260	163	3.7%
1	113	2.6%
Other values (48)	898	20.6%
(Missing)	733	16.8%

Value	Count	Frequency (%)
0	270	20.2%
52	91	6.8%
12	78	5.8%
104	67	5.0%
24	67	5.0%
364	63	4.7%
1	59	4.4%
2	41	3.1%
156	35	2.6%
3	34	2.5%
Other values (27)	179	13.4%
(Missing)	355	26.5%

Value	Count	Frequency (%)
0	473	10.8%
1	113	2.6%
2	104	2.4%
3	102	2.3%
4	61	1.4%

Value	Count	Frequency (%)
0	270	20.2%
1	59	4.4%
2	41	3.1%
3	34	2.5%
4	20	1.5%

Value	Count	Frequency (%)
0	270	6.2%
1	59	1.4%
2	41	0.9%
3	34	0.8%
4	20	0.5%

Value	Count	Frequency (%)
0	473	35.3%
1	113	8.4%
2	104	7.8%
3	102	7.6%
4	61	4.6%

SmokeNow
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.3%
Missing	2653	596
Missing (%)	60.8%	44.5%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	3
Mean length	2.382009346	2.569313594
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	4.078	1.909
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	Yes
2nd row	Yes	No
3rd row	Yes	Yes
4th row	No	No
5th row	No	Yes

Value	Count	Frequency (%)
no	1058	61.8%
yes	654	38.2%

Value	Count	Frequency (%)
yes	423	56.9%
no	320	43.1%

Most occurring characters

Value	Count	Frequency (%)
N	1058	25.9%
o	1058	25.9%
Y	654	16.0%
e	654	16.0%
s	654	16.0%

Value	Count	Frequency (%)
Y	423	22.2%
e	423	22.2%
s	423	22.2%
N	320	16.8%
o	320	16.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4078	100.0%

Value	Count	Frequency (%)
(unknown)	1909	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	1058	25.9%
o	1058	25.9%
Y	654	16.0%
e	654	16.0%
s	654	16.0%

Value	Count	Frequency (%)
Y	423	22.2%
e	423	22.2%
s	423	22.2%
N	320	16.8%
o	320	16.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4078	100.0%

Value	Count	Frequency (%)
(unknown)	1909	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	1058	25.9%
o	1058	25.9%
Y	654	16.0%
e	654	16.0%
s	654	16.0%

Value	Count	Frequency (%)
Y	423	22.2%
e	423	22.2%
s	423	22.2%
N	320	16.8%
o	320	16.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4078	100.0%

Value	Count	Frequency (%)
(unknown)	1909	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	1058	25.9%
o	1058	25.9%
Y	654	16.0%
e	654	16.0%
s	654	16.0%

Value	Count	Frequency (%)
Y	423	22.2%
e	423	22.2%
s	423	22.2%
N	320	16.8%
o	320	16.8%

Smoke100
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	3
Mean length	2.392210767	2.55489171
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	10.442	3.421
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	No
2nd row	No	Yes
3rd row	Yes	No
4th row	No	No
5th row	No	Yes

Value	Count	Frequency (%)
no	2653	60.8%
yes	1712	39.2%

Value	Count	Frequency (%)
yes	743	55.5%
no	596	44.5%

Most occurring characters

Value	Count	Frequency (%)
N	2653	25.4%
o	2653	25.4%
Y	1712	16.4%
e	1712	16.4%
s	1712	16.4%

Value	Count	Frequency (%)
Y	743	21.7%
e	743	21.7%
s	743	21.7%
N	596	17.4%
o	596	17.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	10442	100.0%

Value	Count	Frequency (%)
(unknown)	3421	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	2653	25.4%
o	2653	25.4%
Y	1712	16.4%
e	1712	16.4%
s	1712	16.4%

Value	Count	Frequency (%)
Y	743	21.7%
e	743	21.7%
s	743	21.7%
N	596	17.4%
o	596	17.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	10442	100.0%

Value	Count	Frequency (%)
(unknown)	3421	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	2653	25.4%
o	2653	25.4%
Y	1712	16.4%
e	1712	16.4%
s	1712	16.4%

Value	Count	Frequency (%)
Y	743	21.7%
e	743	21.7%
s	743	21.7%
N	596	17.4%
o	596	17.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	10442	100.0%

Value	Count	Frequency (%)
(unknown)	3421	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	2653	25.4%
o	2653	25.4%
Y	1712	16.4%
e	1712	16.4%
s	1712	16.4%

Value	Count	Frequency (%)
Y	743	21.7%
e	743	21.7%
s	743	21.7%
N	596	17.4%
o	596	17.4%

Smoke100n
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	< 0.1%	0.1%
Missing	0	0
Missing (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	10	10
Median length	10	6
Mean length	8.43115693	7.780433159
Min length	6	6

Characters and Unicode

	Dataset A	Dataset B
Total characters	36.802	10.418
Distinct characters	9	9
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Non-Smoker	Non-Smoker
2nd row	Non-Smoker	Smoker
3rd row	Smoker	Non-Smoker
4th row	Non-Smoker	Non-Smoker
5th row	Non-Smoker	Smoker

Value	Count	Frequency (%)
non-smoker	2653	60.8%
smoker	1712	39.2%

Value	Count	Frequency (%)
smoker	743	55.5%
non-smoker	596	44.5%

Most occurring characters

Value	Count	Frequency (%)
o	7018	19.1%
S	4365	11.9%
m	4365	11.9%
k	4365	11.9%
e	4365	11.9%
r	4365	11.9%
N	2653	7.2%
n	2653	7.2%
-	2653	7.2%

Value	Count	Frequency (%)
o	1935	18.6%
S	1339	12.9%
m	1339	12.9%
k	1339	12.9%
e	1339	12.9%
r	1339	12.9%
N	596	5.7%
n	596	5.7%
-	596	5.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	36802	100.0%

Value	Count	Frequency (%)
(unknown)	10418	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	7018	19.1%
S	4365	11.9%
m	4365	11.9%
k	4365	11.9%
e	4365	11.9%
r	4365	11.9%
N	2653	7.2%
n	2653	7.2%
-	2653	7.2%

Value	Count	Frequency (%)
o	1935	18.6%
S	1339	12.9%
m	1339	12.9%
k	1339	12.9%
e	1339	12.9%
r	1339	12.9%
N	596	5.7%
n	596	5.7%
-	596	5.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	36802	100.0%

Value	Count	Frequency (%)
(unknown)	10418	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	7018	19.1%
S	4365	11.9%
m	4365	11.9%
k	4365	11.9%
e	4365	11.9%
r	4365	11.9%
N	2653	7.2%
n	2653	7.2%
-	2653	7.2%

Value	Count	Frequency (%)
o	1935	18.6%
S	1339	12.9%
m	1339	12.9%
k	1339	12.9%
e	1339	12.9%
r	1339	12.9%
N	596	5.7%
n	596	5.7%
-	596	5.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	36802	100.0%

Value	Count	Frequency (%)
(unknown)	10418	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	7018	19.1%
S	4365	11.9%
m	4365	11.9%
k	4365	11.9%
e	4365	11.9%
r	4365	11.9%
N	2653	7.2%
n	2653	7.2%
-	2653	7.2%

Value	Count	Frequency (%)
o	1935	18.6%
S	1339	12.9%
m	1339	12.9%
k	1339	12.9%
e	1339	12.9%
r	1339	12.9%
N	596	5.7%
n	596	5.7%
-	596	5.7%

SmokeAge
Real number (ℝ)

	Dataset A	Dataset B
Distinct	34	36
Distinct (%)	2.1%	5.0%
Missing	2744	613
Missing (%)	62.9%	45.8%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	18.24861197	17.19283747

	Dataset A	Dataset B
Minimum	7	6
Maximum	50	72
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	7	6
5-th percentile	13	10
Q1	15	14
median	18	16
Q3	20	18
95-th percentile	27	28.5
Maximum	50	72
Range	43	66
Interquartile range (IQR)	5	4

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	4.70295477	6.548177188
Coefficient of variation (CV)	0.2577157527	0.380866579
Kurtosis	7.02812305	15.72308138
Mean	18.24861197	17.19283747
Median Absolute Deviation (MAD)	2	2
Skewness	1.973801112	3.255806362
Sum	29581	12482
Variance	22.11778357	42.87862449
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
18	250	5.7%
16	189	4.3%
15	188	4.3%
19	146	3.3%
17	144	3.3%
20	128	2.9%
14	112	2.6%
21	70	1.6%
22	69	1.6%
13	66	1.5%
Other values (24)	259	5.9%
(Missing)	2744	62.9%

Value	Count	Frequency (%)
16	107	8.0%
18	100	7.5%
15	99	7.4%
17	67	5.0%
14	65	4.9%
13	52	3.9%
12	40	3.0%
20	29	2.2%
19	22	1.6%
25	19	1.4%
Other values (26)	126	9.4%
(Missing)	613	45.8%

Value	Count	Frequency (%)
7	3	0.1%
9	1	< 0.1%
10	13	0.3%
11	10	0.2%
12	45	1.0%

Value	Count	Frequency (%)
6	4	0.3%
7	1	0.1%
8	3	0.2%
9	13	1.0%
10	19	1.4%

Value	Count	Frequency (%)
6	4	0.1%
7	1	< 0.1%
8	3	0.1%
9	13	0.3%
10	19	0.4%

Value	Count	Frequency (%)
7	3	0.2%
9	1	0.1%
10	13	1.0%
11	10	0.7%
12	45	3.4%

Marijuana
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.3%
Missing	1374	602
Missing (%)	31.5%	45.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	3	3
Mean length	2.601136744	2.519674355
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	7.780	1.857
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Yes	Yes
2nd row	Yes	No
3rd row	No	No
4th row	No	Yes
5th row	Yes	Yes

Value	Count	Frequency (%)
yes	1798	60.1%
no	1193	39.9%

Value	Count	Frequency (%)
yes	383	52.0%
no	354	48.0%

Most occurring characters

Value	Count	Frequency (%)
Y	1798	23.1%
e	1798	23.1%
s	1798	23.1%
N	1193	15.3%
o	1193	15.3%

Value	Count	Frequency (%)
Y	383	20.6%
e	383	20.6%
s	383	20.6%
N	354	19.1%
o	354	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7780	100.0%

Value	Count	Frequency (%)
(unknown)	1857	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	1798	23.1%
e	1798	23.1%
s	1798	23.1%
N	1193	15.3%
o	1193	15.3%

Value	Count	Frequency (%)
Y	383	20.6%
e	383	20.6%
s	383	20.6%
N	354	19.1%
o	354	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7780	100.0%

Value	Count	Frequency (%)
(unknown)	1857	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	1798	23.1%
e	1798	23.1%
s	1798	23.1%
N	1193	15.3%
o	1193	15.3%

Value	Count	Frequency (%)
Y	383	20.6%
e	383	20.6%
s	383	20.6%
N	354	19.1%
o	354	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7780	100.0%

Value	Count	Frequency (%)
(unknown)	1857	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	1798	23.1%
e	1798	23.1%
s	1798	23.1%
N	1193	15.3%
o	1193	15.3%

Value	Count	Frequency (%)
Y	383	20.6%
e	383	20.6%
s	383	20.6%
N	354	19.1%
o	354	19.1%

AgeFirstMarij
Real number (ℝ)

	Dataset A	Dataset B
Distinct	31	25
Distinct (%)	1.7%	6.5%
Missing	2568	956
Missing (%)	58.8%	71.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	17.42404007	16.32375979

	Dataset A	Dataset B
Minimum	1	7
Maximum	48	46
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	1	7
5-th percentile	13	11
Q1	15	14
median	17	16
Q3	19	18
95-th percentile	24	25
Maximum	48	46
Range	47	39
Interquartile range (IQR)	4	4

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	3.679601377	4.261680526
Coefficient of variation (CV)	0.2111795751	0.2610722395
Kurtosis	10.92391899	6.513142938
Mean	17.42404007	16.32375979
Median Absolute Deviation (MAD)	2	2
Skewness	2.046133828	1.603072708
Sum	31311	6252
Variance	13.5394663	18.16192091
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
16	293	6.7%
18	282	6.5%
15	202	4.6%
17	182	4.2%
19	176	4.0%
14	140	3.2%
20	121	2.8%
13	81	1.9%
21	76	1.7%
12	64	1.5%
Other values (21)	180	4.1%
(Missing)	2568	58.8%

Value	Count	Frequency (%)
15	56	4.2%
16	55	4.1%
18	39	2.9%
17	34	2.5%
13	33	2.5%
12	32	2.4%
14	31	2.3%
19	18	1.3%
20	15	1.1%
11	10	0.7%
Other values (15)	60	4.5%
(Missing)	956	71.4%

Value	Count	Frequency (%)
1	1	< 0.1%
9	2	< 0.1%
10	6	0.1%
11	10	0.2%
12	64	1.5%

Value	Count	Frequency (%)
7	2	0.1%
8	2	0.1%
9	3	0.2%
10	9	0.7%
11	10	0.7%

Value	Count	Frequency (%)
7	2	< 0.1%
8	2	< 0.1%
9	3	0.1%
10	9	0.2%
11	10	0.2%

Value	Count	Frequency (%)
1	1	0.1%
9	2	0.1%
10	6	0.4%
11	10	0.7%
12	64	4.8%

RegularMarij
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.3%
Missing	1374	602
Missing (%)	31.5%	45.0%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	2
Mean length	2.242059512	2.335142469
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	6.706	1.721
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	Yes
2nd row	No	No
3rd row	No	No
4th row	No	Yes
5th row	No	No

Value	Count	Frequency (%)
no	2267	75.8%
yes	724	24.2%

Value	Count	Frequency (%)
no	490	66.5%
yes	247	33.5%

Most occurring characters

Value	Count	Frequency (%)
N	2267	33.8%
o	2267	33.8%
Y	724	10.8%
e	724	10.8%
s	724	10.8%

Value	Count	Frequency (%)
N	490	28.5%
o	490	28.5%
Y	247	14.4%
e	247	14.4%
s	247	14.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6706	100.0%

Value	Count	Frequency (%)
(unknown)	1721	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	2267	33.8%
o	2267	33.8%
Y	724	10.8%
e	724	10.8%
s	724	10.8%

Value	Count	Frequency (%)
N	490	28.5%
o	490	28.5%
Y	247	14.4%
e	247	14.4%
s	247	14.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6706	100.0%

Value	Count	Frequency (%)
(unknown)	1721	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	2267	33.8%
o	2267	33.8%
Y	724	10.8%
e	724	10.8%
s	724	10.8%

Value	Count	Frequency (%)
N	490	28.5%
o	490	28.5%
Y	247	14.4%
e	247	14.4%
s	247	14.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6706	100.0%

Value	Count	Frequency (%)
(unknown)	1721	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	2267	33.8%
o	2267	33.8%
Y	724	10.8%
e	724	10.8%
s	724	10.8%

Value	Count	Frequency (%)
N	490	28.5%
o	490	28.5%
Y	247	14.4%
e	247	14.4%
s	247	14.4%

AgeRegMarij
Real number (ℝ)

	Dataset A	Dataset B
Distinct	27	23
Distinct (%)	3.7%	9.3%
Missing	3641	1092
Missing (%)	83.4%	81.6%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	18.09392265	16.88259109

	Dataset A	Dataset B
Minimum	11	8
Maximum	52	50
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	11	8
5-th percentile	13	11.3
Q1	16	14
median	17	16
Q3	20	19
95-th percentile	25	25
Maximum	52	50
Range	41	42
Interquartile range (IQR)	4	5

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	4.585987024	4.774421662
Coefficient of variation (CV)	0.25345455	0.2828014749
Kurtosis	12.24465662	13.83557993
Mean	18.09392265	16.88259109
Median Absolute Deviation (MAD)	2	2
Skewness	2.697248206	2.496684371
Sum	13100	4170
Variance	21.03127698	22.7951022
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
16	123	2.8%
18	113	2.6%
15	81	1.9%
20	69	1.6%
17	69	1.6%
19	50	1.1%
21	36	0.8%
14	35	0.8%
13	34	0.8%
22	25	0.6%
Other values (17)	89	2.0%
(Missing)	3641	83.4%

Value	Count	Frequency (%)
16	35	2.6%
18	27	2.0%
14	24	1.8%
17	23	1.7%
15	23	1.7%
12	20	1.5%
19	18	1.3%
20	17	1.3%
13	16	1.2%
25	10	0.7%
Other values (13)	34	2.5%
(Missing)	1092	81.6%

Value	Count	Frequency (%)
11	3	0.1%
12	23	0.5%
13	34	0.8%
14	35	0.8%
15	81	1.9%

Value	Count	Frequency (%)
8	3	0.2%
9	1	0.1%
10	7	0.5%
11	2	0.1%
12	20	1.5%

Value	Count	Frequency (%)
8	3	0.1%
9	1	< 0.1%
10	7	0.2%
11	2	< 0.1%
12	20	0.5%

Value	Count	Frequency (%)
11	3	0.2%
12	23	1.7%
13	34	2.5%
14	35	2.6%
15	81	6.0%

HardDrugs
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.2%
Missing	835	484
Missing (%)	19.1%	36.1%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	2
Mean length	2.175637394	2.222222222
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	7.680	1.900
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Yes	No
2nd row	No	No
3rd row	No	No
4th row	No	Yes
5th row	No	No

Value	Count	Frequency (%)
no	2910	82.4%
yes	620	17.6%

Value	Count	Frequency (%)
no	665	77.8%
yes	190	22.2%

Most occurring characters

Value	Count	Frequency (%)
N	2910	37.9%
o	2910	37.9%
Y	620	8.1%
e	620	8.1%
s	620	8.1%

Value	Count	Frequency (%)
N	665	35.0%
o	665	35.0%
Y	190	10.0%
e	190	10.0%
s	190	10.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7680	100.0%

Value	Count	Frequency (%)
(unknown)	1900	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	2910	37.9%
o	2910	37.9%
Y	620	8.1%
e	620	8.1%
s	620	8.1%

Value	Count	Frequency (%)
N	665	35.0%
o	665	35.0%
Y	190	10.0%
e	190	10.0%
s	190	10.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7680	100.0%

Value	Count	Frequency (%)
(unknown)	1900	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	2910	37.9%
o	2910	37.9%
Y	620	8.1%
e	620	8.1%
s	620	8.1%

Value	Count	Frequency (%)
N	665	35.0%
o	665	35.0%
Y	190	10.0%
e	190	10.0%
s	190	10.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7680	100.0%

Value	Count	Frequency (%)
(unknown)	1900	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	2910	37.9%
o	2910	37.9%
Y	620	8.1%
e	620	8.1%
s	620	8.1%

Value	Count	Frequency (%)
N	665	35.0%
o	665	35.0%
Y	190	10.0%
e	190	10.0%
s	190	10.0%

SexEver
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.2%
Missing	837	480
Missing (%)	19.2%	35.8%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	3	3
Mean length	2.966269841	2.95459837
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	10.465	2.538
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Yes	Yes
2nd row	Yes	Yes
3rd row	Yes	Yes
4th row	Yes	Yes
5th row	Yes	Yes

Value	Count	Frequency (%)
yes	3409	96.6%
no	119	3.4%

Value	Count	Frequency (%)
yes	820	95.5%
no	39	4.5%

Most occurring characters

Value	Count	Frequency (%)
Y	3409	32.6%
e	3409	32.6%
s	3409	32.6%
N	119	1.1%
o	119	1.1%

Value	Count	Frequency (%)
Y	820	32.3%
e	820	32.3%
s	820	32.3%
N	39	1.5%
o	39	1.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Value	Count	Frequency (%)
(unknown)	2538	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
Y	3409	32.6%
e	3409	32.6%
s	3409	32.6%
N	119	1.1%
o	119	1.1%

Value	Count	Frequency (%)
Y	820	32.3%
e	820	32.3%
s	820	32.3%
N	39	1.5%
o	39	1.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Value	Count	Frequency (%)
(unknown)	2538	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
Y	3409	32.6%
e	3409	32.6%
s	3409	32.6%
N	119	1.1%
o	119	1.1%

Value	Count	Frequency (%)
Y	820	32.3%
e	820	32.3%
s	820	32.3%
N	39	1.5%
o	39	1.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	10465	100.0%

Value	Count	Frequency (%)
(unknown)	2538	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
Y	3409	32.6%
e	3409	32.6%
s	3409	32.6%
N	119	1.1%
o	119	1.1%

Value	Count	Frequency (%)
Y	820	32.3%
e	820	32.3%
s	820	32.3%
N	39	1.5%
o	39	1.5%

SexAge
Real number (ℝ)

	Dataset A	Dataset B
Distinct	34	28
Distinct (%)	1.0%	3.4%
Missing	959	520
Missing (%)	22.0%	38.8%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	17.94862008	16.36752137

	Dataset A	Dataset B
Minimum	9	9
Maximum	50	39
Zeros	0	0
Zeros (%)	0.0%	0.0%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	9	9
5-th percentile	13	12
Q1	16	14
median	17	16
Q3	19	18
95-th percentile	25	23
Maximum	50	39
Range	41	30
Interquartile range (IQR)	3	4

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	3.722614484	3.84262162
Coefficient of variation (CV)	0.2074039378	0.2347711381
Kurtosis	8.456029555	6.716275225
Mean	17.94862008	16.36752137
Median Absolute Deviation (MAD)	2	2
Skewness	1.878693348	1.878930775
Sum	61133	13405
Variance	13.85785859	14.76574091
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
17	539	12.3%
16	530	12.1%
18	526	12.1%
19	341	7.8%
15	324	7.4%
20	239	5.5%
14	177	4.1%
21	131	3.0%
22	104	2.4%
13	89	2.0%
Other values (24)	406	9.3%
(Missing)	959	22.0%

Value	Count	Frequency (%)
15	134	10.0%
16	113	8.4%
18	96	7.2%
14	89	6.6%
17	89	6.6%
13	75	5.6%
12	46	3.4%
20	38	2.8%
19	38	2.8%
21	19	1.4%
Other values (18)	82	6.1%
(Missing)	520	38.8%

Value	Count	Frequency (%)
9	26	0.6%
10	5	0.1%
11	16	0.4%
12	49	1.1%
13	89	2.0%

Value	Count	Frequency (%)
9	13	1.0%
10	9	0.7%
11	8	0.6%
12	46	3.4%
13	75	5.6%

Value	Count	Frequency (%)
9	13	0.3%
10	9	0.2%
11	8	0.2%
12	46	1.1%
13	75	1.7%

Value	Count	Frequency (%)
9	26	1.9%
10	5	0.4%
11	16	1.2%
12	49	3.7%
13	89	6.6%

SexNumPartnLife
Real number (ℝ)

	Dataset A	Dataset B
Distinct	66	57
Distinct (%)	1.9%	6.8%
Missing	852	501
Missing (%)	19.5%	37.4%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	12.44577284	22.91885442

	Dataset A	Dataset B
Minimum	0	0
Maximum	999	1000
Zeros	139	45
Zeros (%)	3.2%	3.4%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	1	0
Q1	2	3
median	5	7
Q3	11	15
95-th percentile	40	80.75
Maximum	999	1000
Range	999	1000
Interquartile range (IQR)	9	12

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	38.50161935	81.33235267
Coefficient of variation (CV)	3.093549901	3.548709338
Kurtosis	429.1728557	103.5473532
Mean	12.44577284	22.91885442
Median Absolute Deviation (MAD)	4	5
Skewness	18.45706433	9.486362244
Sum	43722	19206
Variance	1482.374692	6614.951592
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	515	11.8%
3	352	8.1%
5	343	7.9%
2	238	5.5%
6	236	5.4%
10	224	5.1%
4	194	4.4%
7	147	3.4%
0	139	3.2%
8	138	3.2%
Other values (56)	987	22.6%
(Missing)	852	19.5%

Value	Count	Frequency (%)
1	80	6.0%
3	76	5.7%
5	73	5.5%
2	57	4.3%
10	52	3.9%
15	49	3.7%
0	45	3.4%
4	44	3.3%
20	44	3.3%
8	42	3.1%
Other values (47)	276	20.6%
(Missing)	501	37.4%

Value	Count	Frequency (%)
0	139	3.2%
1	515	11.8%
2	238	5.5%
3	352	8.1%
4	194	4.4%

Value	Count	Frequency (%)
0	45	3.4%
1	80	6.0%
2	57	4.3%
3	76	5.7%
4	44	3.3%

Value	Count	Frequency (%)
0	45	1.0%
1	80	1.8%
2	57	1.3%
3	76	1.7%
4	44	1.0%

Value	Count	Frequency (%)
0	139	10.4%
1	515	38.5%
2	238	17.8%
3	352	26.3%
4	194	14.5%

SexNumPartYear
Real number (ℝ)

	Dataset A	Dataset B
Distinct	17	14
Distinct (%)	0.6%	1.9%
Missing	1382	607
Missing (%)	31.7%	45.3%
Infinite	0	0
Infinite (%)	0.0%	0.0%
Mean	1.1615823	1.841530055

	Dataset A	Dataset B
Minimum	0	0
Maximum	20	69
Zeros	518	133
Zeros (%)	11.9%	9.9%
Negative	0	0
Negative (%)	0.0%	0.0%
Memory size	197.2 KiB	53.2 KiB

Quantile statistics

	Dataset A	Dataset B
Minimum	0	0
5-th percentile	0	0
Q1	1	1
median	1	1
Q3	1	1
95-th percentile	3	5
Maximum	20	69
Range	20	69
Interquartile range (IQR)	0	0

Descriptive statistics

	Dataset A	Dataset B
Standard deviation	1.524901436	5.278251779
Coefficient of variation (CV)	1.312779505	2.866231678
Kurtosis	63.16123643	95.28194479
Mean	1.1615823	1.841530055
Median Absolute Deviation (MAD)	0	0
Skewness	6.7809007	9.064146077
Sum	3465	1348
Variance	2.32532439	27.85994184
Monotonicity	Not monotonic	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	2084	47.7%
0	518	11.9%
2	209	4.8%
3	73	1.7%
5	31	0.7%
4	19	0.4%
8	14	0.3%
6	7	0.2%
10	6	0.1%
9	4	0.1%
Other values (7)	18	0.4%
(Missing)	1382	31.7%

Value	Count	Frequency (%)
1	457	34.1%
0	133	9.9%
2	52	3.9%
3	45	3.4%
5	14	1.0%
6	7	0.5%
30	6	0.4%
4	4	0.3%
9	4	0.3%
50	2	0.1%
Other values (4)	8	0.6%
(Missing)	607	45.3%

Value	Count	Frequency (%)
0	518	11.9%
1	2084	47.7%
2	209	4.8%
3	73	1.7%
4	19	0.4%

Value	Count	Frequency (%)
0	133	9.9%
1	457	34.1%
2	52	3.9%
3	45	3.4%
4	4	0.3%

Value	Count	Frequency (%)
0	133	3.0%
1	457	10.5%
2	52	1.2%
3	45	1.0%
4	4	0.1%

Value	Count	Frequency (%)
0	518	38.7%
1	2084	155.6%
2	209	15.6%
3	73	5.5%
4	19	1.4%

SameSex
['Text', 'Text']

	Dataset A	Dataset B
Distinct	2	2
Distinct (%)	0.1%	0.2%
Missing	835	481
Missing (%)	19.1%	35.9%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	3	3
Median length	2	2
Mean length	2.076770538	2.064102564
Min length	2	2

Characters and Unicode

	Dataset A	Dataset B
Total characters	7.331	1.771
Distinct characters	5	5
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	No	No
2nd row	No	No
3rd row	No	No
4th row	No	No
5th row	No	No

Value	Count	Frequency (%)
no	3259	92.3%
yes	271	7.7%

Value	Count	Frequency (%)
no	803	93.6%
yes	55	6.4%

Most occurring characters

Value	Count	Frequency (%)
N	3259	44.5%
o	3259	44.5%
Y	271	3.7%
e	271	3.7%
s	271	3.7%

Value	Count	Frequency (%)
N	803	45.3%
o	803	45.3%
Y	55	3.1%
e	55	3.1%
s	55	3.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7331	100.0%

Value	Count	Frequency (%)
(unknown)	1771	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	3259	44.5%
o	3259	44.5%
Y	271	3.7%
e	271	3.7%
s	271	3.7%

Value	Count	Frequency (%)
N	803	45.3%
o	803	45.3%
Y	55	3.1%
e	55	3.1%
s	55	3.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7331	100.0%

Value	Count	Frequency (%)
(unknown)	1771	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	3259	44.5%
o	3259	44.5%
Y	271	3.7%
e	271	3.7%
s	271	3.7%

Value	Count	Frequency (%)
N	803	45.3%
o	803	45.3%
Y	55	3.1%
e	55	3.1%
s	55	3.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7331	100.0%

Value	Count	Frequency (%)
(unknown)	1771	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	3259	44.5%
o	3259	44.5%
Y	271	3.7%
e	271	3.7%
s	271	3.7%

Value	Count	Frequency (%)
N	803	45.3%
o	803	45.3%
Y	55	3.1%
e	55	3.1%
s	55	3.1%

SexOrientation
['Text', 'Text']

	Dataset A	Dataset B
Distinct	3	3
Distinct (%)	0.1%	0.4%
Missing	1406	646
Missing (%)	32.2%	48.2%
Memory size	197.2 KiB	53.2 KiB

Length

	Dataset A	Dataset B
Max length	12	12
Median length	12	12
Mean length	11.87563366	11.85858586
Min length	8	8

Characters and Unicode

	Dataset A	Dataset B
Total characters	35.140	8.218
Distinct characters	13	13
Distinct categories	1	1 ?
Distinct scripts	1	1 ?
Distinct blocks	1	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

	Dataset A	Dataset B
Unique	0	0 ?
Unique (%)	0.0%	0.0%

Sample

	Dataset A	Dataset B
1st row	Heterosexual	Heterosexual
2nd row	Heterosexual	Heterosexual
3rd row	Heterosexual	Heterosexual
4th row	Heterosexual	Heterosexual
5th row	Heterosexual	Heterosexual

Value	Count	Frequency (%)
heterosexual	2839	95.9%
bisexual	64	2.2%
homosexual	56	1.9%

Value	Count	Frequency (%)
heterosexual	665	96.0%
bisexual	21	3.0%
homosexual	7	1.0%

Most occurring characters

Value	Count	Frequency (%)
e	8637	24.6%
s	2959	8.4%
x	2959	8.4%
u	2959	8.4%
a	2959	8.4%
l	2959	8.4%
o	2951	8.4%
H	2895	8.2%
t	2839	8.1%
r	2839	8.1%
Other values (3)	184	0.5%

Value	Count	Frequency (%)
e	2023	24.6%
s	693	8.4%
x	693	8.4%
u	693	8.4%
a	693	8.4%
l	693	8.4%
o	679	8.3%
H	672	8.2%
t	665	8.1%
r	665	8.1%
Other values (3)	49	0.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	35140	100.0%

Value	Count	Frequency (%)
(unknown)	8218	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	8637	24.6%
s	2959	8.4%
x	2959	8.4%
u	2959	8.4%
a	2959	8.4%
l	2959	8.4%
o	2951	8.4%
H	2895	8.2%
t	2839	8.1%
r	2839	8.1%
Other values (3)	184	0.5%

Value	Count	Frequency (%)
e	2023	24.6%
s	693	8.4%
x	693	8.4%
u	693	8.4%
a	693	8.4%
l	693	8.4%
o	679	8.3%
H	672	8.2%
t	665	8.1%
r	665	8.1%
Other values (3)	49	0.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	35140	100.0%

Value	Count	Frequency (%)
(unknown)	8218	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	8637	24.6%
s	2959	8.4%
x	2959	8.4%
u	2959	8.4%
a	2959	8.4%
l	2959	8.4%
o	2951	8.4%
H	2895	8.2%
t	2839	8.1%
r	2839	8.1%
Other values (3)	184	0.5%

Value	Count	Frequency (%)
e	2023	24.6%
s	693	8.4%
x	693	8.4%
u	693	8.4%
a	693	8.4%
l	693	8.4%
o	679	8.3%
H	672	8.2%
t	665	8.1%
r	665	8.1%
Other values (3)	49	0.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	35140	100.0%

Value	Count	Frequency (%)
(unknown)	8218	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	8637	24.6%
s	2959	8.4%
x	2959	8.4%
u	2959	8.4%
a	2959	8.4%
l	2959	8.4%
o	2951	8.4%
H	2895	8.2%
t	2839	8.1%
r	2839	8.1%
Other values (3)	184	0.5%

Value	Count	Frequency (%)
e	2023	24.6%
s	693	8.4%
x	693	8.4%
u	693	8.4%
a	693	8.4%
l	693	8.4%
o	679	8.3%
H	672	8.2%
t	665	8.1%
r	665	8.1%
Other values (3)	49	0.6%

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks